"List of Publications"
Home | Personal | Education | Work | Research | Publications | Students | Search






I have been featured in many news items in the corresponding media. Most of them are listed below.
NEWS ITEMS

Overview of Publications and Research Interests

I currently have over 405 publications, which include book chapters, and refereed publications which have appeared (or will appear) as either journal or conference papers. They reflect the results that I have obtained in the various areas that I have worked in, and with those whom I have collaborated over the years. To see the entire list of the areas, and the specific results click here.

JOURNAL PUBLICATIONS

  1. Sakhravi, R., Omran, M. T. and Oommen, B. J., On the Existence and Heuristic Computation of the Solution for the Commons Game. To appear in Transactions on Computational Collective Intelligence. (Acceped June 3, 2014).

  2. Zhang, X., Granmo, O-C., Oommen, B. J. and Jiao, L., A Formal Proof of the Epsilon-Optimality of Absorbing Continuous Pursuit Algorithms Using the Theory of Regular Functions. To appear in Applied Intelligence. (Acceped March 19, 2014).

  3. Yazidi, A., Granmo, O-C., Oommen, B. J. and Goodwin, M., A Novel Strategy for Solving the Stochastic Point Location Problem Using a Hierarchical Searching Scheme. To appear in IEEE Transactions on Systems, Man and Cybernetics. (Acceped December 28, 2013).

  4. Astudillo, C. and Oommen, B. J., Topology-Oriented Self-Organizing Maps: A Survey, Pattern Analysis and Applications Journal, Vol. 17, 2014, pp. 223-248.

  5. Astudillo, C. and Oommen, B. J., Self Organizing Maps Whose Topologies Can Be Learned With Adaptive Binary Search Trees Using Conditional Rotations, Pattern Recognition, Vol. 47, 2014, pp. 96-113.

  6. Oommen, B. J. and Thomas, A., Pattern Classification Using Order Statistics Criteria for Some Members of the Exponential Family, Pattern Recognition, Vol. 47, 2014, pp. 40-55.

  7. Qin, K. and Oommen, B. J., Logistic Neural Networks: Their Chaotic and Pattern Recognition Properties, Neurocomputing, Vol. 125, 2014, pp. 184-194.

  8. Qin, K. and Oommen, B. J., Chaotic Neural Networks with a Random Topology Can Achieve Pattern Recognition, Chaotic Modeling and Simulation, Vol. 4, 2013, pp. 583-590.

  9. Calitoiu, D. and Oommen, B. J., On Utilizing Nonlinear Interdependence Measures for Analyzing Chaotic Behavior in Large-Scale Neuro-Models, Chaotic Modeling and Simulation, Vol. 3, 2013, pp. 423-430.

  10. Stensby, A., Oommen, B. J. and Granmo, O-C., The Use of Weak Estimators to Achieve Language Detection and Tracking in Multilingual Documents, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 27, 2013, 1350011 (33 pages).

  11. Zhang, X., Granmo, O-C. and Oommen, B. J., On Incorporating the Paradigms of Discretization and Bayesian Estimation to Create a New Family of Pursuit Learning Automata, Applied Intelligence, Vol. 39, 2013, pp. 782-792.

  12. Oommen, B. J. and Hashem, K., Modeling the "Learning Process" of the Teacher in a Tutorial-like System Using Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. 43, 2013, pp. 2020-2031.

  13. Thomas, A. and Oommen, B. J., Order Statistics-based Parametric Classification for Multi-dimensional Distributions, Pattern Recognition, 2013, pp. 3472-3482.

  14. Qin, K. and Oommen, B. J., Ideal Chaotic Pattern Recognition Is Achievable: The Ideal-M-AdNN - Its Design and Properties, Transactions on Computational Collective Intelligence, 2013, pp. 22-51.

  15. Yazidi, A., Granmo, O-C. and Oommen, B. J., Learning Automaton Based On-line Discovery and Tracking of Spatio-Temporal Event Patterns, IEEE Transactions on Systems, Man and Cybernetics, Vol. 43, 2013, pp. 1118-1130.

  16. Astudillo, C. and Oommen, B. J., On Achieving Semi-supervised Pattern Recognition by Utilizing Tree-Based SOMs, Pattern Recognition, Vol. 46, 2013, pp. 293-304.

  17. Oommen, B. J. and Fayyoumi, E., On Utilizing Dependence-Based Information to Enhance Micro-Aggregation for Secure Statistical Databases, Pattern Analysis and Applications, Vol. 16, 2013, pp. 99-116.

  18. Thomas, A. and Oommen, B. J., The Fundamental Theory of Optimal "Anti-Bayesian" Parametric Pattern Classification Using Order Statistics Criteria, Pattern Recognition, Vol. 46, 2013, pp. 376-388.

  19. Calitoiu, D., Oommen, B. J. and Nussbaum, D., Large Scale Neuro-modeling for Understanding and Controlling Brain-related Chaotic Behavior, Simulation: Transactions of the Society for Modeling and Simulation International, Vol. 88, 2012, pp. 1316-1337.

  20. Oommen, B. J. and Hashem, K., Modeling a Teacher in a Tutorial-like System Using Learning Automata, Transactions on Computational Collective Intelligence, Vol. 8, 2012, pp. 37-62.

  21. Oommen, B. J., Yazidi, A. and Granmo, O-C., An Adaptive Approach to Learning the Preferences of Users in a Social Network Using Weak Estimators, Journal of Information Processing Systems, Vol. 8, 2012, pp. 707-728.

  22. Yazidi, A., Granmo, O-C. and Oommen, B. J., Service Selection in Stochastic Environments: A Learning-Automaton Based Solution, Applied Intelligence, Vol. 36, 2012, pp. 617-637.

  23. Oommen, B. J., Granmo, O-C. and Pedersen, A., Achieving Unbounded Resolution in Finite Player Goore Games using Stochastic Automata, and its Applications, Sequential Analysis, Vol. 31, 2012, pp. 190-218.

  24. Kim, S-W. and Oommen, B. J., On Using Prototype Reduction Schemes to Optimize Locally Linear Reconstruction Methods, Pattern Recognition, Vol. 45, 2012, pp. 498-511.

  25. Qin, K. and Oommen, B. J., The Entire Range of Chaotic Pattern Recognition Properties Possessed by the Adachi Neural Network, International Journal of Intelligent Decision Technologies, Vol. 6, 2012, pp. 27-41.

  26. Bellinger, C. and Oommen, B. J., On the Pattern Recognition and Classification of Stochastically Episodic Events, Transactions on Computational Collective Intelligence, Vol. 6, 2012, pp. 1-35.

  27. Yazidi, A., Granmo, O-C. and Oommen, B. J., On the Analysis of a Random Interleaving Walk-Jump Process with Applications to Testing, Sequential Analysis, Vol. 30, 2011, pp. 457-478.

  28. Yazidi, A., Granmo, O-C. , Oommen, B. J., Gerdes, M. and Reichert, F., A User-centric Approach for Personalized Service Provisioning in Pervasive Environments, Wireless Personal Communication, Vol. 61, 2011, pp. 543-566.

  29. Granmo, O-C. and Oommen, B. J., Learning Automata-based Solutions to the Optimal Web Polling Problem Modelled as a Nonlinear Fractional Knapsack Problem, Engineering Applications of Artificial Intelligence, Vol. 24, 2011, pp. 1238-1251.

  30. Astudillo, C. and Oommen, B. J., Imposing Tree-based Topologies onto Self Organizing Maps, Information Sciences, Vol. 181, 2011, pp. 3798-3815.

  31. Fayyoumi, E. and Oommen, B. J., A Survey on Statistical Disclosure Control and Micro-Aggregation Techniques for Secure Statistical Databases, Software: Practice and Experience, Vol. 40, 2010, pp. 1161-1188.

  32. Aygun, E., Oommen, B. J. and Cataltepe, Z., Peptide Classification Using Optimal and Information Theoretic Syntactic Modeling Pattern Recognition, Pattern Recognition, Vol. 43, 2010, pp. 3891-3899.

  33. Granmo, O-C. and Oommen, B. J., Optimal Sampling for Estimation with Constrained Resources Using a Learning Automaton-based Solution for the Nonlinear Fractional Knapsack Problem, Applied Intelligence, Vol. 33, 2010, pp. 3-20.

  34. Oommen, B. J. and Hashem, K., Modeling a Domain in a Tutorial-like System Using Learning Automata, Acta Cybernetica, Vol. 19, 2010, pp. 635-653.

  35. Rueda, L. and Oommen, B. J. and Henriquez, C., Multi-class Pairwise Linear Dimensionality Reduction Using Heteroscedastic Schemes, Pattern Recognition, July 2010, pp. 2456-2465.

  36. Misra, S. and Oommen, B. J., Fault-Tolerant Routing In Adversarial Mobile Ad Hoc Networks: An Efficient Route Estimation Scheme For Non-Stationary Environments, Telecommunication Systems Journal, June 2010, pp. 159-169.

  37. Granmo, O-C. and Oommen, B. J., Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata, IEEE Transactions on Computers, Vol. TC-59, April 2010, pp. 545-560.

  38. Oommen, B. J. and Hashem, K., Modeling a Student's Behavior in a Tutorial-like System Using Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-40(B), April 2010, pp. 481-492.

  39. Horn, G. and Oommen, B. J., Solving Multi-Constraint Assignment Problems Using Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-40(B), February 2010, pp. 6-18.

  40. Oommen, B. J. and Hashem, K., Modeling a Student-Classroom Interaction in a Tutorial-like System Using Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-40(B), February 2010, pp. 29-42.

  41. Misra, S., Oommen, B. J., Yanamandra, S. and Obaidat, M. S., Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-40(B), February 2010, pp. 66-76.

  42. Fayyoumi, E. and Oommen, B. J., On Utilizing Association and Interaction Concepts for Enhancing Micro-Aggregation in Secure Statistical Databases, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-40(B), February 2010, pp. 198-207.

  43. Qin, K. and Oommen, B. J., Adachi-like Chaotic Neural Networks Requiring Linear-time Computations by Enforcing a Tree-shaped Topology, IEEE Transactions on Neural Networks, Vol. 20, November 2009, pp. 1797-1809.

  44. Kim, S-W. and Oommen, B. J., On Using Prototype Reduction Schemes to Enhance the Computation of Volume-based Inter-Class Overlap Measures, Pattern Recognition, November 2009, pp. 2695-2704.

  45. Fayyoumi, E. and Oommen, B. J., Achieving Micro-Aggregation for Secure Statistical Databases Using Fixed Structure Partitioning-Based Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-39(B), October 2009, pp. 1192-1205.

  46. Misra, S. and Oommen, B. J., Using Pursuit Automata for Estimating Stable Shortest Paths in Stochastic Network Environments, International Journal of Communication Systems, Vol. 22, 2009, pp. 441-468.

  47. Zhu, Q. and Oommen, B. J., Estimation of Distributions Involving Unobservable Events : The Case of Optimal Search With Unknown Target Distributions, Pattern Analysis and Applications Journal, 2009, pp. 37-53.

  48. Rueda, L. and Oommen, B. J., An Efficient Compression Scheme for Data Communication Which Uses a New Family of Self-Organizing Binary Search Trees, International Journal of Communication Systems, June 2008, pp. 1091-1120.

  49. Kim, S-W. and Oommen, B. J., On Using Prototype Reduction Schemes to Optimize Kernel-based Fisher Discriminant Analysis, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-38(B), April 2008, pp. 564-570.

  50. Oommen, B. J., Kim, S-W., Samuel, M. and Granmo, O-C., A Solution to the Stochastic Point Location Problem in Meta-Level Non-Stationary Environments, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-38(B), April 2008, pp. 466-476.

  51. Calitoiu, D., Oommen, B. J. and Nussbaum D., Spikes Annihilation in the Hodgkin-Huxley Neuron , Journal of Biological Cybernetics, Vol. SMC-38(B), March 2008, pp. 239-257.

  52. Oommen, B. J., Kim, S-W. and Horn, G., On the Estimation of Independent Binomial Random Variables Using Occurrence and Sequential Information , Pattern Recognition, November 2007, pp. 3263-3276.

  53. Kim, S-W. and Oommen, B. J., On Using Prototype Reduction Schemes to Optimize Dissimilarity-based Classification, Pattern Recognition, November 2007, pp. 2946-2957.

  54. Oommen, B. J., Misra, S. and Granmo, O-C., Routing Bandwidth Guaranteed Paths in MPLS Traffic Engineering: A Multiple Race Track Learning Approach, IEEE Transactions on Computers, July 2007, pp. 959-976.

  55. Calitoiu, D., Oommen, B. J. and Nussbaum, D., Periodicity and Stability Issues of a Chaotic Pattern Recognition Neural Network, Pattern Analysis and Applications Journal, July 2007, pp. 175-188.

  56. Calitoiu, D., Oommen, B. J. and , Nussbaum, D., Desynchronizing a Chaotic Pattern Recognition Neural Network to Model Inaccurate Perception, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-37(B), July 2007, pp. 692-704.

  57. Amer, A. and Oommen, B. J., A Novel Framework for Self-Organizing Lists in Environments with Locality of Reference: Lists-on-Lists, The Computer Journal, March 2007, pp. 186-196.

  58. Atrey, P. K., Kankanhalli, M. S. and Oommen, B. J., Goal-oriented Optimal Subset Selection of Correlated Multimedia Streams, ACM TOMCCAP, the ACM Transactions on Multimedia Computing, Communications and Applications, Vol. 3, No. 1, Article 2, February 2007, pp 1-24.

  59. Oommen, B. J. and Badr, G., Breadth-First Search Strategies for Trie-Based Syntactic Pattern Recognition, Pattern Analysis and Applications Journal, Vol. 10, February 2007, pp. 1-13.

  60. Granmo, O-C., Oommen, B. J., Myrer, S. A. and Olsen, M. G., Learning Automata-Based Solutions to the Nonlinear Fractional Knapsack Problem With Applications to Optimal Resource Allocation, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-37(B), February 2007, pp. 166-175.

  61. Rueda, L. and Oommen, B. J., Stochastic Automata-based Estimators for Adaptively Compressing Files with Non-Stationary Distributions, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-36(B), October 2006, pp. 1196-1200.

  62. Badr, G. and Oommen, B. J., A Novel Look-Ahead Optimization Strategy for Trie-Based Approximate String Matching, Pattern Analysis and Applications Journal, Volume 9, September 2006, pp. 177-187.

  63. Oommen, B. J., Raghunath, G. and Kuipers, B., Parameter Learning from Stochastic Teachers and Stochastic Compulsive Liars, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-36(B), August 2006, pp. 820-836.

  64. Misra, S. and Oommen, B. J., An Efficient Dynamic Algorithm For Maintaining All-Pairs Shortest Paths In Stochastic Networks, IEEE Transactions on Computers, Vol. TC-55, June 2006, pp. 686-702

  65. Badr, G. and Oommen, B. J., On Optimizing Syntactic Pattern Recognition using Tries and AI-based Heuristic Search Strategies, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-36(B), June 2006, pp. 611-622.

  66. Rueda, L. and Oommen, B. J., A Fast and Efficient Nearly-Optimal Adaptive Fano Coding Scheme, Information Sciences, Vol. 176, 2006, pp. 1656-1683.

  67. Oommen, B. J. and Rueda, L., Stochastic Learning-based Weak Estimation of Multinomial Random Variables and Its Applications to Pattern Recognition in Non-stationary Environments, Pattern Recognition, Vol. 39, 2006, pp. 328-341.

  68. Kim, S-W. and Oommen, B. J., Prototype Reduction Schemes Applicable for Non-stationary Data Sets, Pattern Recognition, Vol. 39, 2006, pp 209-222.

  69. Misra, S. and Oommen, B. J., Dynamic Algorithms for the Shortest Path Routing Problem : Learning Automata-based Solutions, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-35(B), June 2005, pp. 1179-1192.

  70. Badr, G. and Oommen, B. J., Self-Adjusting of Ternary Search Tries Using Conditional Rotations and Randomized Heuristics, The Computer Journal, Vol. 48, March 2005, pp. 200-219. This paper was cited as being Most Meritorious, and was a winner of one of the Wilkes Best Paper Awards in 2006 by the journal The Computer Journal.

  71. Oommen, B. J. and Rueda, L., A Formal Analysis of Why Heuristic Functions Work, The Artificial Intelligence Journal, Vol. 164, 2005, pp. 1-22.

  72. Kim, S-W. and Oommen, B. J., On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, 2005, pp. 455-460.

  73. Kim, S-W. and Oommen, B. J., On Utilizing Search Methods to Select Subspace Dimensions for Kernel-based Nonlinear Subspace Classifiers, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, 2005, pp. 136-141.

  74. Ouerd, M., Oommen, B. J. and Matwin, S., A Formal Approach to Using Data Distributions for Building Causal Polytree Structures, Information Sciences, Vol. 168, 2004, pp. 111-132.

  75. Misra, S. and Oommen, B. J., GPSPA : A New Adaptive Algorithm for Maintaining Shortest Path Routing Trees in Stochastic Networks, International Journal of Communication Systems, Vol. 17, September 2004, pp. 963-984.

  76. Kim, S-W. and Oommen, B. J., Enhancing Prototype Reduction Schemes with Recursion : A Method Applicable for "Large" Data Sets, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-34(B), June 2004, pp. 1384-1397.

  77. Rueda, L. and Oommen, B. J., A Nearly-Optimal Fano-based Coding Algorithm, Information Processing and Management, Vol. 40, 2004, pp. 257-268.

  78. Kim, S-W. and Oommen, B. J., On Using Prototype Reduction Schemes to Optimize Kernel-Based Nonlinear Subspace Methods, Pattern Recognition, Vol. 37, no. 2, pp. 227-239, 2004.

  79. Oommen, B. J. and Thiyagarajah, M., Benchmarking Attribute Cardinality Maps for Database Systems Using the TPC-D Specifications, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-33(B), December 2003, pp. 913-924.

  80. Aras, N., Altinel, I. K., and Oommen, B. J., A Kohonen-Like Decomposition Method for the Euclidean Traveling Salesman Problem -- KNIES_DECOMPOSE, IEEE Transactions on Neural Networks, Vol. 14, 2003, pp. 869-890.

  81. Kim, S-W. and Oommen, B. J., A Brief Taxonomy and Ranking of Creative Prototype Reduction Schemes, Pattern Analysis and Applications Journal, 2003, pp. 232-244.

  82. Kim, S-W. and Oommen, B. J., Enhancing Prototype Reduction Schemes with LVQ3-Type Algorithms, Pattern Recognition, Vol. 36, 2003, pp. 1083-1093.

  83. Rueda, L. and Oommen, B. J., On Optimal Pairwise Linear Classifiers for Normal Distributions: The d-Dimensional Case, Pattern Recognition, Vol. 36, 2003, pp. 13-23. The downloaded file is the unabridged version.

  84. Oommen, B. J. and Roberts, T. D., A Discretized Learning Automata Solutions to the Capacity Assignment Problem for Prioritized Networks, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-32(B), December 2002, pp. 821-831.

  85. Agache, M. and Oommen, B. J., Generalized Pursuit Learning Schemes : New Families of Continuous and Discretized Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-32(B), December 2002, pp. 738-749.

  86. Oommen, B. J. and Rueda, L., The Efficiency of Modern-day Histogram-like Techniques for Query Optimization, The Computer Journal, Vol. 45, 2002, pp. 494-510.

  87. Racherla, G., Radhakrishnan, S. and Oommen, B. J., Enhanced Layered Segment Trees : A Pragmatic Data Structure for Real-Time Processing of Geometric Objects, Pattern Recognition, Vol. 35, 2002, pp. 2303-2309.

  88. Rueda, L. and Oommen, B. J., On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case, IEEE Transactions on Pattern Analysis and Machine Intelligence , Vol. PAMI-24, February 2002, pp. 274-280. The downloaded file is the unabridged version.

  89. Oommen, B. J. and Loke, R. K. S., On the Pattern Recognition of Noisy Subsequence Trees, IEEE Transactions on Pattern Analysis and Machine Intelligence , Vol. PAMI-23, September 2001, pp. 929-946.

  90. Zhu, Q., Zhou, M. and Oommen, B. J., Some Results on Optimal Search in Discrete and Continuous Spaces, Journal of Software, Vol.12, No.12, 2001, pp. 1748-1752.

  91. Oommen, B. J. and Agache, M., Continuous and Discretized Pursuit Learning Schemes: Various Algorithms and Their Comparison, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-31(B), June 2001, pp. 277-287.

  92. Oommen, B. J. and Roberts, T. D., Continuous Learning Automata Solutions to the Capacity Assignment Problem, IEEE Transactions on Computers, Vol. 49:6, June 2000, pp. 608-620.

  93. Altinel, I. K., Aras, N. and Oommen, B. J., Fast, Efficient and Accurate Solutions to the Hamiltonian Path Problem Using Neural Approaches, Computers and Operations Research, Vol. 27, 2000, pp. 461-494.

  94. Oommen, B. J. and Loke, R. K. S., Designing Syntactic Pattern Classifiers Using Vector Quantization and Parametric String Editing, IEEE Transactions on Systems, Man and Cybernetics , Vol. SMC-29(B), December 1999, pp. 881-888.

  95. Aras, N., Oommen, B. J., and Altinel, I. K., The Kohonen Network Incorporating Explicit Statistics and Its Application to the Traveling Salesman Problem, Neural Networks, Vol. 12, October 1999, pp 1273-1284.

  96. Oommen, B.J. and Raghunath, G., Automata Learning and Intelligent Tertiary Searching for Stochastic Point Location, IEEE Transactions on Systems, Man and Cybernetics , Vol. SMC-28(B), 1998, pp. 947-954.

  97. Oommen, B.J. and Kashyap, R.L., A Formal Theory for Optimal and Information Theoretic Syntactic Pattern Recognition, Pattern Recognition , Vol. 31, 1998, pp. 1159-1177. This paper won the "Honorable Mention of the Year" Paper Award in 1998 by the journal Pattern Recognition.

  98. Oommen, B. J. Altinel, I. K., Aras, N, Discrete Vector Quantization for Arbitrary Distance Function Estimation, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-28(B), 1998, pp. 496-510.

  99. Oommen, B.J. and Loke, R., Pattern Recognition of Strings With Substitutions, Insertions, Deletions and Generalized Transpositions, Pattern Recognition, Vol. 30, 1997, pp. 789-800.

  100. Altinel, I. K., Oommen, B. J., Aras, N., Vector Quantization for Arbitrary Distance Function Estimation, ORSA Journal of Computing, Vol. 9, 1997, pp. 439-451.

  101. Oommen, B. J., Stochastic Searching on the Line and its Applications to Parameter Learning in Nonlinear Optimization, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-27(B), August 1997, pp. 733-739.

  102. Oommen, B. J. and De St. Croix, T., String Taxonomy Using Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-27(B), April 1997, pp. 354-365.

  103. Nguyen, T. and Oommen, B.J., Moment Preserving Piece-Wise Linear Approximations of Signals and Images, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-19, 1997, pp. 84-91.

  104. Oommen, B.J., Zhang, K. and Lee, W., Numeric Similarity and Dissimilarity Measures between Two Trees, IEEE Transactions on Computers, Vol.TC-45, December 1996, pp. 1426-1434.

  105. Oommen, B. J. and Zhang,, K. The Normalized String Editing Problem Revisited, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-18, June 1996, pp. 669-672.

  106. Oommen, B.J. and De St. Croix, T., Graph Partitioning Using Learning Automata, IEEE Transactions on Computers, Vol. TC-45, No. 2, 1995, pp. 195-208.

  107. Valiveti, R.S., Oommen, B.J. and Zgierski, J., Adaptive Linear List Reorganization Under a Generalized Query System, Journal of Applied Probability, Vol.32, 1995, pp. 793-804.

  108. Oommen, B.J and Masum, H., Switching Models for Non-Stationary Random Environments, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-25, No. 9, 1995, pp. 1334-1339.

  109. Sum, S.T. and Oommen, B.J., Mixture Decomposition for Distributions from the Exponential Family using A Generalized Method of Moments, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-25, No. 7, 1995, pp. 1139-1149.

  110. Oommen, B.J., String Alignment With Substitution, Insertion, Deletion, Squashing and Expansion Operations, Information Sciences, Vol. 77 March 1995, pp. 89-107.

  111. Oommen, B.J. and Lee, W., Constrained Tree Editing, Information Sciences, Vol. 77 March 1994, pp. 253-273.

  112. Oommen, B.J. and Ng, D.T.H., A New Technique For Enhancing Data Retrieval : Reorganize Data Using Artificially Synthesized Queries, The Computer Journal, Vol. 37, No. 7, 1994, pp. 598-609.

  113. Oommen, B.J. and Zgierski, J., SEATER: An Object-Oriented Simulation Environment Using Learning Automata For Telephone Traffic Routing, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-24, No. 2,1994, pp. 349-356.

  114. Ng, D.T.H., Oommen, B.J. and Hansen, E.R., Adaptive Learning Mechanisms for Ordering Actions Using Random Races, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-23, No. 5, 1993, pp. 1450-1465.

  115. Oommen, B.J. and Ng, D.T.H., An Optimal Absorbing List Organization Strategy with Constant Memory Requirements, Theoretical Computer Science, Vol. 119, 1993, pp. 355-361.

  116. Oommen, B.J. and Fothergill, C., Fast Learning Automaton-Based Image Examination and Retrieval, The Computer Journal, Vol. 36, No. 6, 1993, pp. 542-553.

  117. Cheetham, R.P., Oommen, B.J. and Ng, D.T.H., Adaptive Structuring of Binary Search Trees Using Conditional Rotations, IEEE Transactions on Knowledge and Data Engineering, Vol. 5, No. 4, 1993, pp. 695-704.

  118. Valiveti, R.S. and Oommen, B.J., Determining Stochastic Dependence for Normally Distributed Vectors Using the Chi-Squared Metric, Pattern Recognition, Vol. 26, No. 6, 1993, pp. 975-987.

  119. Oommen, B.J., Transforming Ill-Conditioned Constrained Problems Using Projections, The Computer Journal, Vol. 36, No. 3, 1993, pp. 282-285.

  120. Oommen, B.J. and Zgierski, J., A Learning Automaton Solution to Breaking Substitution Cyphers, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-15, February 1993, pp. 185-192.

  121. Valiveti, R.S. and Oommen, B.J., Self-Organizing Doubly-Linked Lists, Journal of Algorithms, Vol. 14, 1993, pp. 88-114.

  122. Valiveti, R.S. and Oommen, B.J., On Using the Chi-Squared Metric for Determining Stochastic Dependence, Pattern Recognition, Vol. 25, No. 11, 1992, pp. 1389-1400.

  123. Lanctôt, J.K. and Oommen, B.J., Discretized Estimator Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-22, November/December 1992, pp. 1473-1483.

  124. Ng, D.T.H. and Oommen, B.J., A Short Note On Doubly-Linked List Reorganizing Heuristics, The Computer Journal, Vol.35, No.5, 1992, pp. 533-535.

  125. Oommen, B.J. and Reichstein, I., On the Problem of Multiple Mobile Robots Cluttering a Workspace, Information Sciences, Vol. 63, September 1992, pp. 55-85.

  126. Oommen, B.J. and Ma, D.C.Y., Stochastic Automata Solutions to the Object Partitioning Problem, The Computer Journal, Vol. 35, 1992, pp. A105-A120.

  127. Oommen, B.J., Valiveti, R.S. and Zgierski, J., An Adaptive Learning Solution to the Keyboard Optimization Problem, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-21, November/December 1991, pp. 1608-1618. (Corrected version in IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-22, September/October 1992, pp. 1233-1243).

  128. Valiveti, R.S. and Oommen, B.J., Recognizing Sources of Random Strings, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-13, April 1991, pp. 386-394.

  129. Oommen, B.J., Andrade, N. and Iyengar S.S., Trajectory Planning of Robot Manipulators in Noisy Workspaces Using Stochastic Automata, International Journal of Robotics Research, April 1991, pp. 135-148.

  130. Oommen, B.J. and Ng, D.T.H., On Generating Random Permutations with Arbitrary Distributions, The Computer Journal, Vol 33, No. 4, 1990, pp. 368-374.

  131. Christensen, J.P.R.and Oommen, B.J., Epsilon-Optimal Stubborn Learning Mechanisms, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-20, September/October 1990, pp. 1209-1216.

  132. Oommen, B.J. and Lanctôt, J.K., Discretized Pursuit Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-20, July/August 1990, pp. 431-438.

  133. Oommen, B.J., Hansen, E.R. and Munro, J.I., Deterministic Optimal and Expedient Move-to-Rear List Organizing Strategies, Theoretical Computer Science, Vol. 74, 1990, pp. 183-197.

  134. Rao, S.V.N., Iyengar, S.S., Oommen, B.J. and Kashyap, R.L., On the Terrain Acquisition by a Point Robot Amidst Polyhedral Obstacles, IEEE Journal of Robotics and Automation, August 1988, pp. 450-455.

  135. Oommen, B.J. and Christensen, J.P.R., Epsilon-Optimal Discretized Linear Reward-Penalty Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-18, May/June 1988, pp. 451-458.

  136. Oommen, B.J. and Ma, D.C.Y., Deterministic Learning Automata Solutions to the Equi-Partitioning Problem, IEEE Transactions on Computers, Vol. 37, January 1988, pp. 2-14.

  137. Oommen, B.J., Iyengar, S.S., Rao, S.V.N. and Kashyap, R.L., Robot Navigation in Unknown Terrains Using Learned Visibility Graphs. Part I : The Disjoint Convex Obstacle Case, IEEE Journal of Robotics and Automation, December 1987, pp. 672-681.

  138. Oommen, B.J., Recognition of Noisy Subsequences Using Constrained Edit Distances, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-9, 1987, pp. 676-685. (Corrections to the original paper found in IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. PAMI-10, 1988, pp. 983-984).

  139. Oommen, B.J. and Hansen E.R., List Organizing Strategies using Stochastic Move-to-Front and Stochastic Move-to-Rear Operations, SIAM Journal of Computing, Vol. 16, No. 4, August 1987, pp. 705-716.

  140. Oommen, B.J., Ergodic Learning Automata Capable of Incorporating A Priori Information, IEEE Transactions on Systems, Man and Cybernetics., Vol. SMC-17, July/August 1987, pp. 717-723.

  141. Oommen, B.J. and Reichstein, I.R., On the Problem of Translating an Elliptic Object Through a Workspace of Elliptic Obstacles , Robotica, Vol. 5, 1987, pp. 187-196.

  142. Oommen, B.J., Constrained String Editing, Information Sciences, Vol. 40, 1987, pp. 267-284.

  143. Oommen, B.J., An Efficient Geometric Solution to the Minimum Spanning Circle Problem, Operations Research, Vol. 35, Jan./Feb. 1987, pp. 80-86.

  144. Oommen, B.J., A Learning Automaton Solution to the Stochastic Minimum Spanning Circle Problem , IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-16, July/Aug. 1986, pp. 598-603. 220 Kbytes)

  145. Oommen, B.J., Absorbing and Ergodic Discretized Two Action Learning Automata, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-16, March/April 1986, pp. 282-293.

  146. Oommen, B.J. and Thathachar, M.A.L., Multiaction Learning Automata Possessing Ergodicity of the Mean , Information Sciences, Vol. 35, June 1985, pp. 183-198.

  147. Oommen, B.J. and Hansen, E.R., The Asymptotic Optimality of Discretized Linear Reward-Inaction Learning Automata , IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-14, May/June 1984, pp. 542-545.

  148. Kashyap, R.L. and Oommen, B.J., String Correction Using Probabilistic Methods, Pattern Recognition Letters, March 1984, pp. 147-154.

  149. Thathachar, M.A.L. and Oommen, B.J., Learning Automata Possessing Ergodicity of the Mean: The Two Action Case, IEEE Transactions on Systems, Man and Cybernetics, Vol. SMC-13, Nov./Dec. 1983, pp. 1143-1148.

  150. Kashyap, R.L. and Oommen, B.J., Scale Preserving Smoothing of Polygons, IEEE Transactions on Pattern Analysis and Machine Intelligence, Nov. 1983, pp. 667-671.

  151. Kashyap, R.L. and Oommen, B.J., The Noisy Substring Matching Problem , IEEE Transactions on Software Engg., May 1983, pp. 365-370.

  152. Kashyap, R.L. and Oommen, B.J., Similarity Measures for Sets of Strings, The International Journal of Computer Mathematics, May 1983, pp. 95-104.

  153. Kashyap, R.L. and Oommen, B.J., A Common Basis for Similarity and Dissimilarity Measures Involving Two Strings, The International Journal of Computer Mathematics, March 1983, pp. 17-40.

  154. Kashyap, R.L. and Oommen, B.J., A Geometrical Approach to Polygonal Dissimilarity and Shape Matching , IEEE Transactions on Pattern Analysis and Machine Intelligence, December 1982, pp. 649-654.

  155. Kashyap, R.L. and Oommen, B.J., An Effective Algorithm for String Correction Using Generalized Edit Distances - II. Computational Complexity of the Algorithm and Some Applications, Information Sciences, Vol. 23, April 1981, pp. 201-217.

  156. Kashyap, R.L. and Oommen, B.J., An Effective Algorithm for String Correction Using Generalized Edit Distances - I. Description of the Algorithm and its Optimality, Information Sciences, Vol. 23, March 1981, pp. 123-142.

  157. Thathachar, M.A.L. and Oommen, B.J., Discretized Reward-Inaction Learning Automata, Journal of Cybernetics and Information Sciences, Spring 1979, pp. 24-29.

CONFERENCE PUBLICATIONS

Some of the conference papers are preliminary versions of corresponding journal papers.

  1. Astudillo, C. and Oommen, B. J., Fast BMU Search in SOMs Using Random Hyperplane Trees. To appear in the Proceedings of PRICAI'14, the 2014 Pacific Rim International Conference on Artificial Intelligence, Gold Coast, Australia, December 2014.

  2. Qin, K. and Oommen, B. J., Cryptanalysis of a Cryptographic Algorithm that Utilizes Chaotic Neural Networks. To appear in the Proceedings of ISCIS'14, the 2014 International Symposium on Computer and Information Sciences, Krakow, Poland, October 2014.

  3. Qin, K. and Oommen, B. J., Chaotic Pattern Recognition Using the Modified Adachi Neural Network - In A Small-World Way, Proceedings of CHAOS'14, the 2014 Chaotic Modeling and Simulation International Conference, Lisbon, Portugal, June 2014, pp. 391-398.

  4. Zhang, X., Oommen, B. J., Granmo, O-C. and Lei, J., Using the Theory of Regular Functions to Formally Prove the Epsilon-Optimality of Discretized Pursuit Learning Algorithms, Proceedings of IEA/AIE'14, the 2014 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Kaohsiung, Taiwan, June 2014, pp. 379-388. This paper won the Best Paper Award of the Conference.

  5. Lei, J., Zhang, X., Granmo, O-C. and Oommen, B. J., A Bayesian Learning Automata-based Distributed Channel Selection Scheme for Cognitive Radio Networks, Proceedings of IEA/AIE'14, the 2014 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Kaohsiung, Taiwan, June 2014, pp. 48-57.

  6. Polk, S. and Oommen, B. J., On Enhancing Recent Multi-Player Game Playing Strategies using a Spectrum of Adaptive Data Structures, Proceedings of TAAI'13, the 2013 Conference on Technologies and Applications of Artificial Intelligence, Taipei, Taiwan, December 2013, pp. 164-169.

  7. Li, Y., Oommen, B. J., Ngom, A. and Rueda, L., A New Paradigm for Pattern Classification: Nearest Border Techniques, Proceedings of AI'13, the 2013 Australasian Joint Conference on Artificial Intelligence, Dunedin, New Zealand, December 2013, pp. 441-446.

  8. Thomas, A. and Oommen, B. J., Ultimate Order Statistics-based Prototype Reduction Schemes, Proceedings of AI'13, the 2013 Australasian Joint Conference on Artificial Intelligence, Dunedin, New Zealand, December 2013, pp. 421-433.

  9. Polk, S. and Oommen, B. J., On Applying Adaptive Data Structures to Multi-Player Game Playing, Proceedings of AI'13, the 2013 SGAI International Conference on Artificial Intelligence, Cambridge, England, December 2013, pp. 125-138.

  10. Zhang, X., Jiao, L., Granmo, O-C. and Oommen, B. J., Channel Selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata Approach, Proceedings of PIMRC'13, the 2013 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, London, UK, September 2013, pp. 2372-2377.

  11. Thomas, A. and Oommen, B. J., A Novel Border Identification Algorithm Based on an "Anti-Bayesian" Paradigm, Proceedings of CAIP'13, the 2013 International Conference on Computer Analysis of Images and Patterns, York, UK, August, 2013, pp. 196-203.

  12. Thomas, A. and Oommen, B. J., On Achieving Near-optimal "Anti-Bayesian" Order Statistics-based Classification for Asymmetric Exponential Distributions, Proceedings of CAIP'13, the 2013 International Conference on Computer Analysis of Images and Patterns, York, UK, August, 2013, pp. 368-376.

  13. Zhang, X., Granmo, O-C. and Oommen, B. J., On Using the Theory of Regular Functions to Prove the Epsilon-Optimality of the Continuous Pursuit Learning Automaton, Proceedings of IEA/AIE'13, the 2013 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Amsterdam, Holland, June 2013, pp. 262-271.

  14. Calitoiu, D. and Oommen, B. J., Nonlinear Interdependence (S) Measures used for Exploring Chaotic Behavior in Large-Scale Neuro-Models, Proceedings of CHAOS'13, the 2013 Chaotic Modeling and Simulation International Conference, Istanbul, Turkey, June 2013, pp. 127-134.

  15. Qin, K. and Oommen, B. J., Chaotic Pattern Recognition Using the Adachi Neural Network Modified in a Random Manner, Proceedings of CHAOS'13, the 2013 Chaotic Modeling and Simulation International Conference, Istanbul, Turkey, June 2013, pp. 453-460.

  16. Thomas, A. and Oommen, B. J., Classification of Multi-dimensional Distributions using Order Statistics Criteria, Proceedings of CORES'13, the 2013 Conference on Computer Recognition Systems, Milkow, Poland, May 2013, pp. 19-29.

  17. Thomas, A. and Oommen, B. J., Optimal "Anti-Bayesian" Parametric Pattern Classification Using Order Statistics Criteria, Proceedings of CIARP'12, the 2012 Iberoamerican Congress on Pattern Recognition, Buenos Aires, Argentina, September 2012, pp. 1-13. This talk was a Plenary/Keynote Talk at the Conference.

  18. Thomas, A. and Oommen, B. J., Optimal "Anti-Bayesian" Parametric Pattern Classification for the Exponential Family Using Order Statistics Criteria, Proceedings of ICIAR'12, the 2012 International Conference on Image Analysis and Recognition, Aveiro, Portugal, June 2012, pp. 11-18.

  19. Zhang, X., Granmo, O-C. and Oommen, B. J., Discretized Bayesian Pursuit -- A New Scheme for Reinforcement Learning, Proceedings of IEA/AIE'12, the 2012 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Dalian, China, June 2012, pp. 784-793.

  20. Yazidi, A., Granmo, O-C., Oommen, B. J. and Goodwin, M., A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem, Proceedings of IEA/AIE'12, the 2012 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Dalian, China, June 2012, pp- 774-783.

  21. Yazidi, A., Granmo, O-C. and Oommen, B. J., A Stochastic Search on the Line-Based Solution to Discretized Estimation, Proceedings of IEA/AIE'12, the 2012 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Dalian, China, June 2012, pp. 764-773.

  22. Qin, K. and Oommen, B. J., Ideal Chaotic Pattern Recognition Using the Modified Adachi Neural Network, Proceedings of CHAOS'12, the 2012 Chaotic Modeling and Simulation International Conference, Athens, Greece, June 2012, pp. 499-508.

  23. Sakhravi, R., Omran, M. T. and Oommen, B. J., A Fast Heuristic Solution for the Commons Game, Proceedings of DCAI'12, the 2012 International Symposium on Distributed Computing and Artificial Intelligence, Salamanca, Spain, March 2012, pp. 81-90.

  24. Yazidi, A., Oommen, B. J. and Granmo, O-C., A Novel Stochastic Discretized Weak Estimator Operating in Non-Stationary Environments, Proceedings of ICNC'12-COG, the 2012 International Conference on Computing, Networking and Communications, Cognitive Computing and Networking Symposium, Hawaii, USA, January/February 2012, pp. 364-370.

  25. Astudillo, C. and Oommen, B. J., Semi-Supervised Classification Using Tree-Based Self-Organizing Maps, Proceedings of AI'11, the 2011 Australasian Joint Conference on Artificial Intelligence, Perth, Australia, December 2011, pp. 21-30.

  26. Yazidi, A., Granmo, O-C. and Oommen, B. J., Tracking the Preferences of Users Using Weak Estimators, Proceedings of AI'11, the 2011 Australasian Joint Conference on Artificial Intelligence, Perth, Australia, December 2011, pp. 799-808.

  27. Zhang, X., Granmo, O-C. and Oommen, B. J., Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems, Proceedings of AIAI'11, the 2011 Conference on Artificial Intelligence Applications and Innovations, Corfu, Greece, September 2011, pp. 122-131.

  28. Qin, K. and Oommen, B. J., Networking Logistic Neurons can Yield Chaotic and Pattern Recognition Properties, Proceedings of CIMSA'11, the 2011 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, Ottawa, Canada, September 2011, pp. 134-139.

  29. Zhang, X., Granmo, O-C. and Oommen, B. J., The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata, Proceedings of IEA/AIE'11, the 2011 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Syracuse, USA, June/July 2011, pp. 525-531.

  30. Yazidi, A., Granmo, O-C. , Oommen, B. J., Reichert, F. and Gerdes, M., An Intelligent Architecture for Service Provisioning in Pervasive Environments, Proceedings of INISTA'11, the 2011 International Symposium on Innovations in Intelligent Systems and Applications, Istanbul, Turkey, June 2011, pp. 524-530.

  31. Oommen, B. J., New Histogram-like Techniques for Cardinality Estimation in Database Query Optimization, Proceedings of the Expert and Industry Session of PReMI'11, the 2011 International Conference on Pattern Recognition and Machine Intelligence, Moscow, Russia, June 2011, pp. 17.

  32. Oommen, B. J., On Merging the Fields of Neural Networks and Adaptive Data Structures to Yield New Pattern Recognition Methodologies, Proceedings of PReMI'11, the 2011 International Conference on Pattern Recognition and Machine Intelligence, Moscow, Russia, June 2011, pp. 13-16. This talk was a Plenary/Keynote Talk at the Conference.

  33. Verkhogliad, P. and Oommen, B. J., Using Artificial Intelligence Techniques for Strategy Generation in the Commons Game, Proceedings of HAIS'11, the 2011 International Conference on Hybrid Artificial Intelligence Systems, Wroclaw, Poland, May 2011, pp. 43-50.

  34. Yazidi, A., Granmo, O-C. and Oommen, B. J., A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes, Proceedings of HAIS'11, the 2011 International Conference on Hybrid Artificial Intelligence Systems, Wroclaw, Poland, May 2011, pp. 11-21. This talk was a Plenary/Keynote Talk at the Conference.

  35. Yazidi, A., Granmo, O-C. and Oommen, B. J., On the Analysis of a New Markov Chain Which has Applications in AI and Machine Learning, Proceedings of CCECE'11, the 2011 Annual Canadian Conference on Electrical and Computer Engineering, Niagara Falls, Canada, May 2011, pp. 1553-1558 (EDAS No. (1569)446001).

  36. Bellinger, C., and Oommen, B. J., A New Frontier in Novelty Detection: Pattern Recognition of Stochastically Episodic Events, Proceedings of ACIIDS'11, the 2011 Asian Conference on Intelligent Information and Database Systems, Daegu, Korea, April 2011, pp. 435-444.

  37. Kim, S-W. and Oommen, B. J., On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes, Proceedings of AI'10, the 2010 Australasian Joint Conference on Artificial Intelligence, Adelaide, Australia, December 2010, pp. 153-163.

  38. Yazidi, A., Granmo, O-C., Lin, M., Wen, X., Oommen, B. J., Gerdes, M. and Reichert, F., Learning Automaton Based On-line Discovery and Tracking of Spatio-Temporal Event Patterns, Proceedings of PRICAI10'10, the 2010 Pacific Rim International Conference on Artificial Intelligence, Daegu, Korea, August/September 2010, pp. 327-338.

  39. Stensby, A., Oommen, B. J., and Granmo, O-C., Language Detection and Tracking in Multilingual Documents Using Weak Estimators, Proceedings of SSSPR'10, the 2010 International Symposium on Structural, Syntactic and Statistical Pattern Recognition, Izmir, Turkey, August 2010, pp. 600-609.

  40. Oommen, B. J., On Utilizing Dependence-Tree Modeling in Arbitrary Simulations, Proceedings of SummerSim'10, the 2010 Summer Simulation Multiconference, Ottawa, Canada, July 2010, pp. KeynoteSummaries:1-3. This talk was a Plenary/Keynote Talk at the Conference.

  41. Bellinger, C., and Oommen, B. J., On Simulating Episodic Events Against a Background of Noise-like Non-episodic Events, Proceedings of SummerSim'10, the 2010 Summer Simulation Multiconference, Ottawa, Canada, July 2010, pp. 452-460.

  42. Yazidi, A., Granmo, O-C. and Oommen, B. J., A Learning Automata Based Solution to Service Selection in Stochastic Environments, Proceedings of IEA/AIE'10, the 2010 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Cordoba, Spain, June 2010, pp. 209-218.

  43. Verkhogliad, P. and Oommen, B. J., Potential AI Strategies to Solve the Commons Game: A Position Paper, Proceedings of CanAI'10, the 2010 Canadian Conference on Artificial Intelligence, Ottawa, Canada, May/June 2010, pp. 352-356.

  44. Oommen, B. J., Recent Advances in Learning Automata Systems, Proceedings of ICCET'10, the 2010 International Conference on Computer Engineering and Technology, Chengdu, China, April 2010, pp. V1:62-73. This talk was a Plenary/Keynote Talk at the Conference.

  45. Qin, K. and Oommen, B. J., Chaotic and Pattern Recognition Properties of a Network of Logistic Neurons, Proceedings of ICCET'10, the 2010 International Conference on Computer Engineering and Technology, Chengdu, China, April 2010, pp. V3:82-87.

  46. Calitoiu, D. and Oommen, B. J., Using Simulation and Stochastic Learning for Pattern Recognition when Training Data is Unavailable:The Case of Disease Outbreak, Proceedings of ICAART'10, the 2010 International Conference on Agents and Artificial Intelligence, Valencia, Spain, January 2010, pp. 45-52.

  47. Norheim, T., Braadland, T., Granmo, O-C. and Oommen, B. J. A Generic Solution to Multi-Armed Bernoulli Bandit Problems Based on Random Sampling from Sibling Conjugate Priors, Proceedings of ICAART'10, the 2010 International Conference on Agents and Artificial Intelligence, Valencia, Spain, January 2010, pp. 36-44.

  48. Astudillo, C. and Oommen, B. J., On Using Adaptive Binary Search Trees to Enhance Self Organizing Maps, Proceedings of AI'09, the 2009 Australasian Joint Conference on Artificial Intelligence, Melbourne, Australia, December 2009, pp. 199-209. This paper won the Best Paper Award of the Conference.

  49. Oommen, B. J. and Hashem, K., Learning Automata-based Tutorial-like Systems, Proceedings of KES'09, the 2009 International Conference on Knowledge-Based and Intelligent Information & Engineering Systems, Santiago, Chile, September 2009, pp. 361-374. This talk was a Plenary/Keynote Talk at the Conference.

  50. Aygun, E., Oommen, B. J. and Cataltepe, Z., On Utilizing Optimal and Information Theoretic Syntactic Modeling for Peptide Classification, Proceedings of PRIB'09, the 2009 IAPR International Conference on Pattern Recognition in Bioinformatics, Sheffield, England, September 2009, pp. 24-35.

  51. Zhan, Z., Oommen, J., and Crisostomo, J., Anomaly Detection in Dynamic Social Systems, Proceedings of the 2009 IEEE International Conference on Social Computing, Vancouver, Canada, August 2009, pp. 18-25.

  52. Oommen, B. J., Granmo, O-C. and Liang, Z., A Novel Stochastic Learning-Enhanced Multidimensional Scaling Technique Applicable for Word-Of-Mouth Discussions, Studies in Computational Intelligence (214): Proceedings of Short Papers of IEA/AIE'09, the 2009 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Tainan City, Taiwan, June 2009, pp. 317-322.

  53. Granmo, O-C. and Oommen, B. J., A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling, Proceedings of IEA/AIE'09, the 2009 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Tainan City, Taiwan, June 2009, pp. 523-534. This paper won the Best Paper Award of the Conference.

  54. Qin, K. and Oommen, B. J., An Enhanced Tree-shaped Adachi-like Chaotic Neural Network Requiring Linear-time Computations, Proceedings of CHAOS'09, the 2009 Chaotic Modeling and Simulation International Conference, Charnia, Greece, June 2009. (The proceedings of the conference is available at: http://www.chaos2009.net/proceedings/index.html. The abstract is on pp. 64-65, and paper, listed by authors, is included in the proceedings. The paper number is 160).

  55. Astudillo, C. and Oommen, B. J., A Novel Self Organizing Map Which Utilizes Imposed Tree-Based Topologies, Proceedings of CORES'09, the 2009 Conference on Computer Recognition Systems, Wroclaw, Poland, May 2009, pp. 183-192. This talk was a Plenary/Keynote Talk at the Conference.

  56. Misra, S., Oommen, B. J., Yanamandra, S. and Obaidat, M. S., An Adaptive Learning-Like Solution of Random Early Detection for Congestion Avoidance in Computer Networks, Proceedings of AICCSA'09, the 2009 ACS/IEEE International Conference on Computer Systems and Applications, Rabat, Morocco, May 2009, pp. 485-491.

  57. Qin, K. and Oommen, B. J., Chaotic Pattern Recognition: The Spectrum of Properties of the Adachi Neural Network, Proceedings of SSSPR'08, the 2008 International Symposium on Structural, Syntactic and Statistical Pattern Recognition, Orlando, Florida, December 2008, pp. 540-550.

  58. Oommen, B. J. and Fayyoumi, E., An AI-Based Causal Strategy for Securing Statistical Databases Using Micro-Aggregation, Proceedings of AI'08, the 2008 Australasian Joint Conference on Artificial Intelligence, Auckland, New Zealand, December 2008, pp. 423-434.

  59. Oommen, B. J., On the Differences Between Discretized and Continuous Stochastic Systems as Demonstrated by Learning Automata, Proceedings of SSS'08, the 2008 ISCIE International Symposium on Stochastic Systems Theory and Its Applications, Kyodai Kaikan, Kyoto, Japan, November 2008. This talk was a Plenary/Keynote Talk at the Conference, which is the 40th conference in this series. The Abstract of the talk was on pages 31-33.

  60. Rueda, L., Henriquez, C. and Oommen, B. J., Chernoff-based Multi-class Pairwise Linear Dimensionality Reduction, Proceedings of CIARP'08, the 2008 Iberoamerican Congress on Pattern Recognition, Havana, Cuba, September 2008, pp. 301-308.

  61. Oommen, B. J. and Fayyoumi, E., Enhancing Micro-Aggregation Techniques by Utilizing Dependence-Based Information in Secure Statistical Databases, Proceedings of ACISP`08, the 2008 Australasian Conference on Information Security and Privacy, Wollongong, Australia , July 2008, pp. 404-418.

  62. Granmo, O-C. and Oommen, B. J., A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Web Polling, Proceedings of IEA/AIE'08, the 2008 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Wroclaw, Poland, June 2008, pp. 347-358.

  63. Kim, S-W. and Oommen, B. J., A Fast Computation of Inter-Class Overlap Measures Using Prototype Reduction Schemes, Proceedings of CanAI'08, the 2008 Canadian Conference on Artificial Intelligence, Windsor, Canada, May 2008, pp. 173-184.

  64. Oommen, B. J. and Calitoiu, D., Modeling and Simulating a Disease Outbreak by Learning a Contagion Parameter-based Model, Proceedings of ICHSS'08, the 2008 International Conference on Health Sciences Simulation, Ottawa, Canada, April 2008, pp. 547-555. This paper won the Best Paper Award of the Conference.

  65. Calitoiu, D., Nussbaum, D. and Oommen, B. J., Large Scale Modeling of the Piriform Cortex for Analyzing Anti-epileptic Effects, Proceedings of ICHSS'08, the 2008 International Conference on Health Sciences Simulation, Ottawa, Canada, April 2008, pp. 599-608.

  66. Oommen, B. J. and Fayyoumi, E., A Novel Method for Micro-Aggregation in Secure Statistical Databases Using Association and Interaction, Proceedings of ICICS'07, the 2007 International Conference on Information and Communications Security, Zhengzhou, China, December 2007, pp. 126-140.

  67. Calitoiu, D., Oommen, B. J. and Nussbaum, D., Some Analysis on the Network of Bursting Neurons : Quantifying Behavioral Synchronization, Proceedings of AI'07, the 2007 Australian Joint Conference on Artificial Intelligence, Gold Coast, Australia, December 2007, pp. 110-119.

  68. Granmo, O-C. and Oommen, B. J., On Using a Hierarchy of Twofold Resource Allocation Automata to Solve Stochastic Nonlinear Resource Allocation Problems, Proceedings of AI'07, the 2007 Australian Joint Conference on Artificial Intelligence, Gold Coast, Australia, December 2007, pp. 36-47.

  69. Hashem, K. and Oommen, B. J., Using Learning Automata to Model the "Learning Process" of the Teacher in a Tutorial-like System, Proceedings of ISCIS'07, the 2007 International Symposium on Computer and Information Sciences, Ankara, Turkey, November 2007, Paper No. 1.3.C-012, pp. 81-86. (Paper can be found at http://ieeexplore.ieee.org/xpl/tocresult.jsp?isnumber=4456820&isYear=2007)

  70. Rueda, L. and Oommen, B. J., A New Approach to Adaptive Encoding Data using Self-organizing Data Structures, Proceedings of ISCIS'07, the 2007 International Symposium on Computer and Information Sciences, Ankara, Turkey, November 2007, Paper No. 2.3.C-010, pp. 15-20. (Paper can also be found at the IEEE web-site of the previous paper).

  71. Hashem, K. and Oommen, B. J., Using Learning Automata to Model the Behavior of a Teacher in a Tutorial-like System, Proceedings of IEEE-SMC'07, the 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, Canada, October 2007, pp. 76-82.

  72. Hashem, K. and Oommen, B. J., Using Learning Automata to Model a Student-Classroom Interaction in a Tutorial-like System, Proceedings of IEEE-SMC'07, the 2007 IEEE International Conference on Systems, Man and Cybernetics, Montreal, Canada, October 2007, pp. 1177-1182.

  73. Calitoiu, D., Oommen, B. J. and Nussbaum, D., Numerical Results on the Hodgkin-Huxley Neural Network : Spike Annihilation, Proceedings of BVAI'07, the 2007 International Symposium on Brain Vision and Artificial Intelligence, Naples, Italy, October 2007, pp. 378-387.

  74. Hashem, K. and Oommen, B. J., Using Learning Automata to Model a Domain in a Tutorial-like System, Proceedings of ICMLC'07, the 2007 International Conference of Machine Learning and Cybernetics, Hong Kong, August 2007, pp. 112-118.

  75. Horn, G. and Oommen, B. J., Estimation in Feedback Loops by Stochastic Learning, Proceedings of IWAPR’07, the 2007 International Workshop on Advances in Pattern Recognition, Plymouth, UK, July 2007, pp. 3-16. This talk was a Plenary/Keynote Talk at the Conference.

  76. Hashem, K. and Oommen, B. J., On Using Learning Automata to Model a Students Behavior in a Tutorial-like System, Proceedings of IEA/AIE'07, the 2007 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Kyoto, Japan, June 2007, pp. 813-822.

  77. Oommen, B. J., Kim, S-W., Samuel, M. and Granmo, O-C., Stochastic Point Location in Non-Stationary Environments and Its Applications, Proceedings of IEA/AIE'07, the 2007 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Kyoto, Japan, June 2007, pp. 845-854.

  78. Calitoiu, D., Oommen, B. J. and , Nussbaum, D., Analytic Results on the Hodgkin-Huxley Neural Network : Spikes Annihilation, Proceedings of CanAI'07, the 2007 Canadian Conference on Artificial Intelligence, Montreal, Canada, May 2007, pp. 320–331.

  79. Misra, S. and Oommen, B. J., The Pursuit Automaton Approach for Estimating All-Pairs Shortest Paths in Dynamically Changing Networks, Proceedings of FINA'07, the 2007 IEEE International Symposium on Frontiers in Networking with Applications, Niagara Falls, Canada, May 2007, pp. 124-129.

  80. Oommen, B. J., Granmo, O-C. and Pedersen, A., Using Stochastic AI Techniques to Achieve Unbounded Resolution in Finite Player Goore Games and its Applications, Proceedings of IEEE-CIG'07, the 2007 IEEE Symposium on Computational Intelligence and Games, Hawaii, USA, April 2007, pp. 161-167.

  81. Fayyoumi, E. and Oommen, B. J., A Fixed Structure Learning Automaton Micro-Aggregation Technique for Secure Statistical Databases, Proceedings of PSD`06, the 2006 International Conference on Privacy in Statistical Databases, Rome, Italy, December 2006, pp. 114-128.

  82. Oommen, B. J., Granmo, O-C. and Pedersen, A., Empirical Verification of a Strategy for Unbounded Resolution in Finite Player Goore Games, Proceedings of AI'06, the 2006 Australian Joint Conference on Artificial Intelligence, Tasmania, Australia, December 2006, pp. 1252-1258.

  83. Kim, S-W. and Oommen, B. J., On Optimizing Dissimilarity-Based Classification Using Prototype Reduction Schemes, Proceedings of ICIAR'06 - the 2006 International Conference on Image Analysis and Recognition, Voa de Varzim, Portugal, September 2006, pp. 15-28. This talk was a Plenary/Keynote Talk at the Conference.

  84. Oommen, B. J., Kim, S-W. and Horn, G., On the Theory and Applications of Sequence Based Estimation of Independent Binomial Random Variables, Proceedings of SSSPR'06, the 2006 International Symposium on Structural, Syntactic and Statistical Pattern Recognition, Hong Kong, August 2006, pp. 8-21. This talk was a Plenary/Keynote Talk at the Conference.

  85. Kim, S-W. and Oommen, B. J., On Optimizing Kernel-based Fisher Discriminant Analysis Using Prototype Reduction Schemes, Proceedings of SSSPR'06, the 2006 International Symposium on Structural, Syntactic and Statistical Pattern Recognition, Hong Kong, August 2006, pp. 826-834.

  86. Oommen, B. J., and Hashem, K., On Simulating Tutorial-like Systems Using a Learning Automata Philosophy, Proceedings of SummerSim'06, the 2006 Summer Simulation Multiconference, Calgary, Canada, July/August 2006, pp. 473-484. This talk was a Plenary/Keynote talk at the Conference.

  87. Fayyoumi, E. and Oommen, B. J., On Optimizing the k-Ward Micro-Aggregation Technique for Secure Statistical Databases, Proceedings of ACISP'06, the 2006 Australasian Conference on Information Security and Privacy, Melbourne, Australia, July 2006, pp. 324-335.

  88. Granmo, O-C. and Oommen, B. J., On Allocating Limited Sampling Resources Using a Learning Automata-based Solution to the Fractional Knapsack Problem, Proceedings of IIS:IIPW'06, the 2006 International Intelligent Information Processing and Web Mining Conference, Poland, June 2006, pp. 263-272.

  89. Horn, G. and Oommen, B. J., Towards a Learning Automata Solution to the Multi-Constraint Partitioning Problem, Proceedings of IEEE-CIS'06, the 2006 IEEE International Conferences on Cybernetics and Intelligent Systems, Bangkok, Thailand, June 2006, pp. 755-762.

  90. Granmo, O-C. and Oommen, B. J., Determining Optimal Polling Frequency using a Learning Automata-based Solution to the Fractional Knapsack Problem, Proceedings of IEEE-CIS'06, the 2006 IEEE International Conferences on Cybernetics and Intelligent Systems, Bangkok, Thailand, June 2006, pp. 73-79.

  91. Oommen, B. J. and Misra, S., A Fault-Tolerant Routing Algorithm for Mobile Ad Hoc Networks Using a Stochastic Learning-Based Weak Estimation Procedure, Proceedings of WiMob'06, the 2006 IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, Montreal, Canada, June 2006, pp. 31-37.

  92. Oommen, B. J. and Chen, J., On Utilizing Attribute Cardinality Maps to Enhance Query Optimization in the ORACLE Database System, Proceedings of ICEIS'06, the 2006 International Conference on Enterprise Information Systems, Cyprus, May 2006, pp. IS:23-35. This talk was a Plenary/Keynote Talk at the Conference.

  93. Amer, A. and Oommen, B. J., Lists on Lists: A Framework for Self-Organizing Lists in Environments with Locality of Reference, Proceedings of WEA'06, the 2006 International Workshop on Experimental Algorithms, Menorca Island, Spain, May 2006, pp. 109-120.

  94. Oommen, B. J. and Misra, S. and Granmo, O-C., A Stochastic Random-Races Algorithm for Routing in MPLS Traffic Engineering, Proceedings of INFOCOM'06, the 2006 IEEE Conference on Computer Communications, Barcelona, Spain, April 2006, Paper:1568966826, pp:1-10.

  95. Hilaire, X. and Oommen, B. J., The Averaged Mappings Problem: Statement, Applications, and Approximate Solution, Proceedings of ACMSE'06, the 2006 ACM South Eastern Conference, Melbourne, Florida, March 2006, pp. 24-29.

  96. Batalov, D. V. and Oommen, B. J., Turning Lights Out with DQ-Learning, Proceedings of AIA'06, the 2006 IASTED International Multi-Conference on Artificial Intelligence and Applications, Innsbruck, Austria, February 2006, pp. 451-456.

  97. Kim, S-W. and Oommen, B. J., Time-Varying Prototype Reduction Schemes Applicable for Non-stationary Data Sets, Proceedings of AI'05, the 2005 Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 2005, pp. 614-623.

  98. Rueda, L. and Oommen, B. J. Efficient Adaptive Data Compression using Fano Binary Search Trees, Proceedings of ISCIS'05, the 2005 International Symposium on Computer and Information Sciences,, Istanbul, Turkey, October 2005, pp. 768-779.

  99. Oommen, B. J. and Rueda, L. On Utilizing Stochastic Learning Weak Estimators for Training and Classification of Patterns with Non-Stationary Distributions, Proceedings of KI'05, the 2005 German Conference on Artificial Intelligence, Koblenz, Germany, September 2005, pp. 107-120.

  100. Badr, G. and Oommen, B. J., Enhancing Trie-Based Syntactic Pattern Recognition Using AI Heuristic Search Strategies, Proceedings of ICAPR'05, the 2005 International Conference on the Advances of Pattern Recognition, Bath, United Kingdom, August 2005, pp. I:1-17. This talk was a Plenary/Keynote talk at the Conference.

  101. Horn, G. and Oommen, B. J., Generalized Pursuit Learning Automata for Non-Stationary Environments Applied to the Stochastic Static Mapping Problem, Proceedings of CITSA’05, the 2005 International Conference on Cybernetics and Information Technologies, Systems and Applications, Orlando, Florida, July 2005, pp. 91-97.

  102. Calitoiu, D., Oommen, B. J. and , Nussbaum, D., Modeling Inaccurate Perception: Desynchronization Issues of a Chaotic Pattern Recognition Neural Network, Proceedings of SCIA'05, the 2005 Scandinavian Conference in Image Analysis, Joensuu, Finland, June 2005, pp. 821-830.

  103. Misra, S. and Oommen, B. J., New Algorithms for Maintaining Dynamic All-Pairs Shortest Paths, Proceedings of IEEE-SCC'05, the 2005 IEEE Symposium on Computers and Communications, La Manga del Mar Menor, Spain, June 2005, pp. 116-121.

  104. Calitoiu, D., Oommen, B. J. and , Nussbaum, D., Neural Network-based Chaotic Pattern Recognition : Part 1 : Stability and Periodicity Issues, Proceedings of PRIP'05, the 2005 International Conference on Pattern Recognition and Information Processing, Minsk, Belarus, May 2005, pp. 252-259. This talk was a Plenary/Keynote talk at the Conference.

  105. Calitoiu, D., Oommen, B. J. and , Nussbaum, D., Neural Network-based Chaotic Pattern Recognition : Part 2 : Stability and Algorithmic Issues, Proceedings of CORES'05, the 2005 Conference on Computer Recognition Systems, Wroclaw, Poland, May 2005, pp. 3-16. This talk was a Plenary/Keynote talk at the Conference.

  106. Badr, G. and Oommen, B. J., A Look-Ahead Branch and Bound Pruning Scheme for Trie-Based Approximate String Matching, Proceedings of CORES'05, the 2005 Conference on Computer Recognition Systems, Wroclaw, Poland, May 2005, pp. 87-94.

  107. Calitoiu, D., Nussbaum, D. and Oommen, B. J., Investigating Schizophrenia using Local Connectivity Considerations within the Piriform Cortex, Proceedings of CCECE'05, the 2005 Canadian Conference on Electrical and Computer Engineering, Saskatoon, Canada, May 2005, pp. 1673-1677.

  108. Horn, G. and Oommen, B. J., A Fixed-Structure Learning Automaton Solution to the Stochastic Static Mapping Problem, Proceedings of IPDPS’05, the 2005 IEEE International Parallel and Distributed Processing Symposium, Denver, Colorado, April 2005, pp. from 297b. (Available electronically as of April 2005 at http://ieeexplore.ieee.org/iel5/9722/30685/01420272.pdf).

  109. Badr, G. and Oommen, B. J., On Using Conditional Rotations and Randomized Heuristics for Self-Organizing Ternary Search Tries, Proceedings of ACMSE'05, the 2005 ACM South Eastern Conference, Kennesaw, Georgia, March 2005, pp. 1:109-1:115.

  110. Kim, S-W. and Oommen, B. J., Selecting Subspace Dimensions for Kernel-based Nonlinear Subspace Classifiers Using Intelligent Search Methods, Proceedings of AI'04, the 2004 Australian Joint Conference on Artificial Intelligence, Cairns, Australia, December 2004, pp. 1115-1121.

  111. Agache, M. and Oommen, B. J., Generalized TSE: A New Generalized Estimator-based Learning Automaton, Proceedings of IEEE-CIS'04, the 2004 IEEE Conference on Cybernetics and Intelligent Systems Singapore, December 2004, pp. 245-251.

  112. Oommen, B. J. and Rueda, L., On Families of New Adaptive Compression Algorithms Suitable for Time-varying Source Data, Proceedings of ADVIS'04, the 2004 Biennial International Conference on Advances in Information Systems, Izmir, Turkey, October 2004, pp. 234-244.

  113. Oommen, B. J. and Rueda, L., A New Family of Weak Estimators for Training in Non-Stationary Distributions, Proceedings of SSSPR'04, the 2004 International Symposium on Structural, Syntactic and Statistical Pattern Recognition, Lisbon, Portugal, August 2004, pp. 644-652.

  114. Oommen, B. J. and Badr, G., Dictionary-Based Syntactic Pattern Recognition Using Tries, Proceedings of SSSPR'04, the 2004 International Symposium on Structural, Syntactic and Statistical Pattern Recognition, Lisbon, Portugal, August 2004, pp. 251-259.

  115. Misra, S. and Oommen, B. J., Adaptive Algorithms for Network Routing and Traffic Engineering, Proceedings of AAAI‘04, the 2004 National Conference on Artificial Intelligence, San Jose, California, July 2004, pp. 993-994.

  116. Misra, S. and Oommen, B. J., Generalized Pursuit Learning Algorithms for Shortest Path Routing Tree Computation, Proceedings of ISCC'04, the 2004 IEEE Symposium on Computers and Communications, Alexandria, Egypt, June-July 2004, pp. 891-896.

  117. Oommen, B. J., Zgierski, J. R., and Nussbaum, D., Stochastic Sorting Using Deterministic Consecutive and Leader Filters, Proceedings of AMCSE'04, the 2004 International Conference on Algorithmic Mathematics and Computer Science, Las Vegas, Nevada, June 2004, pp. 399-405.

  118. Misra, S. and Oommen, B. J., Stochastic Learning Automata-Based Dynamic Algorithms for the Single Source Shortest Path Problem, Proceedings of IEA/AIE'04, the 2004 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Ottawa, Canada,May 2004, pp. 239-248., (This paper was nominated to be the Best Paper of the Conference).

  119. Wang, Q. and Oommen, B. J., On Designing Pattern Classifiers Using Artificially Created Bootstrap Samples, Proceedings of PRIS'04, the 2004 International Workshop on Pattern Recognition in Information Systems, Porto, Portugal, April 2004, pp. 159-168.

  120. Oommen, B. J., Zgierski, J. R., and Nussbaum, D., Deterministic Majority Filters Applied To Stochastic Sorting, Proceedings of ACMSE'04, the 2004 ACM South Eastern Conference, Huntsville, Alabama, April 2004, pp. 228-233.

  121. Altinel, K., and Aras, N. and Oommen, B. J., An Adaptive Method for Map Reconstruction, Proceedings of EIS'04, the 2004 Conference on Engineering of Intelligent Systems, Madeira, Portugal, February-March 2004, from page 123.

  122. Oommen, B. J., Raghunath, G. and Kuipers, B., On How to Learn from a Stochastic Teacher or a Stochastic Compulsive Liar of Unknown Identity, Proceedings of AI'03, the 2003 Australian Joint Conference on Artificial Intelligence, Perth, Australia, December 2003, pp 24-40. This talk was a Plenary/Keynote talk at the Conference.

  123. Kim, S-W. and Oommen, B. J., On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods, Proceedings of AI'03, the 2003 Australian Joint Conference on Artificial Intelligence, Perth, Australia, December 2003, pp. 783-795.

  124. Altinel, K., and Aras, N. and Oommen, B. J., A Self-Organizing Method For Map Reconstruction, Proceedings of NNSP'03, the 2003 IEEE International Workshop on Neural Networks for Signal Processing, Toulouse, France, September 2003, pp. 677-688.

  125. Oommen, B. J. and Chen, J., A New Histogram Method for Sparse Attributes : The Averaged Rectangular Attribute Cardinality Map, Proceedings of ISICT'03, the 2003 International Symposium on Informtaion and Communication Technologies, Dublin, Ireland, September 2003, pp. 119-125.

  126. Oommen, B. J. and Chen, J., The Bounded Trapezoidal Attribute Cardinality Map and its Application to Query optimization, Proceedings of ICCSI'03, the 2003 International Conference on Computer Science and Informatics, Cary, North Carolina, September 2003, pp. 422-426.

  127. Ouerd, M., Oommen, B. J. and Matwin, S., Enhancing Caching in Distributed Databases Using Intelligent Polytree Representations, Proceedings of CanAI'03, the 2003 Canadian Conference on Artificial Intelligence, Halifax, Canada, June 2003, pp. 498-504.

  128. Wang, Q. and Oommen, B. J., Classification Error-Rate Estimation Using New Pseudo-Sample Bootstrap Methods, Proceedings of PRIS'03, the 2003 International Workshop on Pattern Recognition in Information Systems, Angers, France, April 2003, pp. 96-103.

  129. Kim, S-W. and Oommen, B. J., Optimizing Kernel-based Nonlinear Subspace Methods Using Prototype Reduction Schemes, Proceedings of AI'02, the 2002 Australian Joint Conference on Artificial Intelligence, Canberra, Australia, December 2002, pp. 155-166.

  130. Ouerd, M., Oommen, B. J. and Matwin, S., Data Generation for Testing DAG-Structured Bayesian Networks, Proceedings of IEEE-SMC'02, the 2002 IEEE International Conference on Systems, Man and Cybernetics, Hammamet, Tunisia, October 2002.

  131. Kim, S-W. and Oommen, B. J., Creative Prototype Reduction Schemes : A Taxonomy and Ranking, Proceedings of IEEE-SMC'02, the 2002 IEEE International Conference on Systems, Man and Cybernetics, Hammamet, Tunisia, October 2002.

  132. Kim, S-W. and Oommen, B. J., Recursive Prototype Reduction Schemes Applicable for Large Data Sets, Proceedings of SSPR'02, the 2002 International Symposium on Syntactic and Statistical Pattern Recognition, Windsor, Canada, August 2002, pp. 528-537.

  133. Kim, S-W. and Oommen, B. J., On Using LVQ3-Type Algorithms to Enhance Prototype Reduction Schemes, Proceedings of PRIS'02, the 2002 International Workshop on Pattern Recognition in Information Systems, Alicante, Spain, April 2002, pp. 242-256.

  134. Oommen, B. J. and Rueda, L., Using Pattern Recognition Techniques to Derive a Formal Analysis of Why Heuristics Work, Proceedings of PRIS'02, the 2002 International Workshop on Pattern Recognition in Information Systems, Alicante, Spain, April 2002, pp. 45-58.

  135. Rueda, L. and Oommen, B. J., Greedy Adaptive Fano Coding, Proceedings of IEEE-Aero'02, the 2002 IEEE Aerospace Conference, Big Sky, Montana, March 2002, Paper 10.0407.

  136. Rueda, L. and Oommen, B. J., Resolving Minsky's Paradox : The d-Dimensional Normal Distribution Case, Proceedings of AI'01, the 2001 Australian Joint Conference on Artificial Intelligence, Adelaide, Australia, December 2001, pp. 25-36.

  137. Rueda, L. and Oommen, B. J., Enhanced Static Fano Coding, Proceedings of IEEE-SMC'01, the 2001 IEEE International Conference on Systems, Man and Cybernetics, Tucson, Arizona, October 2001, pp. 2163-2169.

  138. Batalov, D. and Oommen, B. J., On Playing Games Without Knowing the Rules, Proceedings of NAFIPS'01, the 2001 International Conference of the North American Fuzzy Information Processing Society, Vancouver, Canada, July 2001, pp. 1862-1868.

  139. Oommen, B. J. and Wang, Q. Distance Bias Adjustment Bootstrap Estimation for Bhattacharya Error Bound in Classifiers, Proceedings of PRIS'01, the 2001 International Workshop on Pattern Recognition in Information Systems, Seubal, Portugal, July 2001, pp. 103-117

  140. Oommen, B. J., and Rueda, L. Histogram Methods in Query Optimization: The Relation between Accuracy and Optimality, Proceedings of DASFAA'01, the 2001 International Conference on Database Systemss for Advanced Applications, Hong Kong, April 2001, pp. 320-326.

  141. Racherla, G., Radhakrishnan, S. and Oommen, B. J., A New Geometric Tool for Pattern Recognition - An Algorithm for Real-Time Insertion of Layered Segment Trees, Proceedings of ICAPR'01, the 2001 International Conference on the Advances of Pattern Recognition, Rio De Janeiro, Brazil, March 2001, pp. 212-221.

  142. Oommen, B. J. and Wang, Q. Computing the Bhattacharya Error Bound in Classifiers Using Direct Bias Correction Bootstrap Methods, Proceedings of NNA'01, the WSES 2001 International Conference on Neural Networks and Applications, Canary Islands, Spain, February 2001, pp. 70-76.

  143. Ouerd, M., Oommen, B. J. and Matwin, S., A Formalism for Building Causal Polytree Structures Using Data Distributions, Proceedings of ISMIS'00, the 2000 International Symposium on Methodologies for Intelligent Systems, Charlotte, North Carolina, October 2000, pp. 629-637.

  144. Oommen, B. J. and Thiyagarajah, M., On the Use of the Trapezoidal Attribute Cardinality Map for Query Result Size Estimation, Proceedings of IDEAS'00, the 2000 International Database Engineering and Applications Symposium, Yokohama, Japan, September 2000, pp. 236-242.

  145. Rueda, L. and Oommen, B. J., The Foundational Theory of Optimal Bayesian Pairwise Linear Classifiers, Proceedings of SPR'00, the 2000 International Workshop on the Advances in Statistical Techniques in Pattern Recognition, Alicante, Spain, August/September, 2000, pp. 581-590.

  146. Oommen, B. J., Altinel, K. and Aras, N., On Statistically Evaluating the Quality of Empirically-Computed Hamiltonian Path Problem Solutions, Proceedings of EMAI'00, the 2000 Workshop on Empirical Methods in Artificial Intelligence, Berlin, Germany, August 2000, pp. 33-46.

  147. Aras, N. Altinel, K. and Oommen, B. J., A Kohonen-like Decomposition Method for the Traveling Salesman Problem - KNIES_DECOMPOSE, Proceedings of ECAI'00, the 2000 European Conference on Artificial Intelligence, Berlin, Germany, August 2000, pp. 261-265.

  148. Agache, M. and Oommen, B. J., Continuous and Discretized Generalized Pursuit Learning Schemes, Proceedings of SCI'00, the 2000 World Multiconference on Systemics, Cybernetics, Orlando, Florida, July 2000, pp. VII:270-275.

  149. Oommen, B. J. and Rueda, L., An Empirical Comparison of Histogram-like Techniques for Query Optimization, Proceedings of ICEIS'00, the 2000 International Conference on Enterprise Information Systems, Stafford, UK, July 2000, pp. 71-78.

  150. Oommen, B. J. and Agache, M., A Comparison of Continuous and Discretized Pursuit Learning Schemes, Proceedings of IEEE-SMC'99, the 1999 IEEE International Conference on Systems, Man and Cybernetics, Tokyo, Japan, October 1999, pp. IV:1061-1067.

  151. Oommen, B. J., Altinel, K., and Aras, N., Kohonen-like Neural Solutions to the Hamiltonian Path Problem, Proceedings of AICS'99, the 1999 Irish Conference on Artificial Intelligence and Cognitive Science, Cork, Ireland, September 1999, pp. 51-57.

  152. Thiyagarajah, M. and Oommen, B. J., On Using the TPC-D Specifications for Benchmarking Attribute Cardinality Maps for Database Systems, Proceedings of DEXA'99, the 1999 International Conference on Database and Expert Systems Applications, Florence, Italy, August-September 1999, pp. 292-301.

  153. Oommen, B. J. and Thiyagarajah, M., Query Result Size Estimation Using a Novel Histogram-like Technique : The Rectangular Attribute Cardinality Map, Proceedings of IDEAS'99, the 1999 International Database Engineering and Applications Symposium, Montreal, Canada, August 1999, pp. 3-15.

  154. Oommen, B. J. and Roberts, T. D., On Solving The Capacity Assignment Problem Using Continuous Learning Automata, Proceedings of IEA/AIE'99, the 1999 International Conference on Industrial and EngineeringApplications of Artificial Intelligence and Expert Systems, Cairo, Egypt, May-June 1999,May-June 1999, pp. 622-631.

  155. Thiyagarajah, M. and Oommen, B. J., Prototype Validation of the Rectangular Attribute Cardinality Map for Query Optimization in Database Systems, Proceedings of BIS'99, the 1999 International Conference on Business Information Systems, Poznan, Poland, April 1999, pp. 250-262.

  156. Thiyagarajah, M. and Oommen, B. J., Prototype Validation of the Trapezoidal  Attribute Cardinality Map for Query Optimization in Database Systems, Proceedings of ICEIS'99, the 1999 International Conference on Enterprise Information Systems, Setubal, Portugal, March 1999, pp. 156-162.

  157. Oommen, B. J. and Zgierski, J., On Using Stochastic Competitions to Obtain Combinatorial Equivalences Involving Beta Functions, Proceedings of CAM'99, the 1999 Conference on Applied Mathematics , Edmond, Oklahoma, February 1999, pp. 200-210.

  158. Oommen, B. J. and Loke, R. K. S., On the Recognition of Noisy Subsequence Trees, Proceedings of SSPR'98, the 1998 International Symposium on Syntactic and Statistical Pattern Recognition , Sydney, Australia, August 1998, pp. 169-180.

  159. Oommen, B. J. and Roberts, T. D., A Fast and Efficient Solution to the Capacity Assignment Problem using Discretized Learning Automata, Proceedings of IEA/AIE'98, the 1998 International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Benicassim, Spain, June 1998, Vol II: pp. 56-65.

  160. Oommen, B. J., Aras, N. and Altinel, K., Solving the Travelling Salesman Problem using the Kohonen Network Incorporating Explicit Statistics, Proceedings of WIRN/VIETRI'98, the Tenth Italian Workshop on Neural Nets , Vietri sul Mare, Italy, May 1998, pp. 273-282.

  161. Oommen, B. J. and Dong, J., Generalized Swap-with-Parent Schemes for Self-Organizing Sequential Linear Lists, Proceedings of ISAAC'97, the 1997 International Symposium on Algorithms and Computation, Singapore, December 1997, pp. 414-423.

  162. Zhu, Q. and Oommen, B.J., On The Optimal Search Problem: The Case when the Target Distribution is Unknown, Proceedings of SCCC'97, the 1997 International Conference of the Chilean Computer Science Society , Valparaiso, Chile, November 1997, pp. 268-277.

  163. Aras, N., Altinel, I. K. and Oommen, B. J., A New Self-Organizing Approach to the Traveling Salesman Problem, Proceedings of ISCIS'97, the 1997 International Symposium on Computer and Information Sciences, Antalya, Turkey, October 1997, pp. 385-392.

  164. Oommen, B.J. and Loke, R.K.S., On Using Parametric String Distances and Vector Quantization in Designing Syntactic Pattern Recognition Systems, Proceedings of IEEE-SMC'97, the 1997 IEEE International Conference on Systems, Man and Cybernetics, Orlando, Florida, October 1997, pp. 511-517.

  165. Oommen, B. J. Altinel, I. K., Aras, N., Arbitrary Distance Function Estimation Using Discrete Vector Quantization, Proceedings of IEEE-NN'97, the 1997 IEEE International Conference on Neural Networks, Houston, Texas, June 1997, pp. 1272-1277.

  166. Oommen, B.J. and Loke, R. K. S., Optimal and Information Theoretic Syntactic Pattern Recognition for Traditional and Generalized Transposition Errors, Proceedings of FSTTCS'96, The 1996 Symposium on the Foundations of Software Technology and Theoretical Computer Science, Hyderabad, India, December 1996, pp. 224-237.

  167. Oommen, B.J. and Raghunath, G., Stochastic Point Location : A Solution using Learning Automata and Intelligent Tertiary Search, Proceedings of ISAI'96, the 1996 International Symposium on Artificial Intelligence, Cancun, Mexico, November 1996, pp. 221-227.

  168. Oommen, B.J. and Loke, R. K. S., Probabilistic Syntactic Pattern Recognition for Traditional and Generalized Transposition Errors, Proceedings of ICPR'96, the 1996 International Conference on Pattern Recognition, Vienna, Austria, August 1996, pp. 685-689.

  169. Oommen, B.J. and Kashyap, R. L., Optimal and Information Theoretic Syntactic Pattern Recognition for Traditional Errors, Proceedings of SSPR'96, the 1996 International Symposium on Syntactic and Structural Pattern Recognition, Leipzig, Germany, August 1996, pp. 11-20.

  170. Oommen, B.J. and Loke, R. K. S., Noisy Subsequence Recognition Using Constrained String Editing Involving Substitutions, Insertions, Deletions and Generalized Transpositions, Proceedings of ICSC'95, the 1995 International Computer Science Conference : Image Analysis Applications and Computer Graphics, Hong Kong, December 1995, pp. 116-123.

  171. Oommen, B. J., Altinel, I. K., Aras, N, Arbitrary Distance Function Estimation Using Vector Quantization, Proceedings of IEEE-NN'95, the 1995 IEEE International Conference on Neural Networks, Perth, Australia, December 1995, pp. 3062-3067.

  172. Oommen, B.J. and Loke, R. K. S., Pattern Recognition of Strings Containing Traditional and Generalized Transposition Errors, Proceedings of IEEE-SMC'95, the 1995 IEEE International Conference on Systems, Man and Cybernetics, Vancouver, Canada, October 1995, pp. 1154-1159.

  173. Oommen, B.J. and De St. Croix, T., On Using Learning Automata for Fast Graph Partitioning, Proceedings of LATIN'95, the 1995 Latin American Symposium on Theoretical Informatics , Valparaiso, Chile, April 1995, pp. 449-460.

  174. Nguyen, T. and Oommen, B.J., Moment Preserving Piece-Wise Linear Curve Approximations Suitable for Vision and Image Understanding, Proceedings of IAS'95, the 1995 International Conference on Intelligent Autonomous Systems, Karlsruhe, Germany, March 1995, pp. 521-528.

  175. Sum, S.T. and Oommen, B.J., Unsupervised Learning Using A Generalized Method of Moments : A Unified Solution for the Exponential Family, Proceedings of ISCIS'94, the 1994 International Symposium on Computer and Information Sciences, Antalya, Turkey, November 1994, pp. 720-727.

  176. Oommen, B.J. and De St. Croix, T., String Taxonomy Using Object Migrating Automata, Proceedings of SSPR'94, the 1994 International Symposium on Syntactic and Statistical Pattern Recognition, Nahariya, Israel, October 1994, pp. 271-280.

  177. Oommen, B.J., Parameter Learning and its Applications in Nonlinear Optimization, Proceedings of ISNTA'93, the 1993 International Symposium on Nonlinear Theory and its Applications, Hawaii, December 1993, pp. 999-1002.

  178. Oommen, B.J. and Kashyap, R.L., Symbolic Channel Modeling for Noisy Channels which Permit Arbitrary Noise Distributions, Proceedings of ISCIS'93, the 1993 International Symposium on Computer and Information Sciences, Istanbul, Turkey, November 1993, pp. 492-499.

  179. Oommen, B.J., String Editing with Substitution, Insertion, Deletion, Squashing and Expansion Operations, Proceedings of ISCIS'93, the 1993 International Symposium on Computer and Information Sciences, Istanbul, Turkey, November 1993, pp. 284-291.

  180. Oommen, B.J and Masum, H., On Modeling Non-Stationary Random Environments Using Switching Techniques, Proceedings of IEEE-SMC'93, the 1993 IEEE International Conference on Systems, Man and Cybernetics, October 1993, Le Touquet, France, pp. 572-577.

  181. Oommen, B.J. and Lee, W., Tree Editing with Arbitrarily Complex Edit Constraints, Proceedings of ICSC'92, the 1992 International Computer Science Conference : Data and Knowledge Engineering : Theory and Applications, Hong Kong, December 1992, pp. 409-415.

  182. Oommen, B.J. and Lee, W., A Common Basis for Similarity and Dissimilarity Measures Involving Two Trees, Proceedings of ISCIS'92, the 1992 International Symposium on Computer and Information Sciences, Antalya, Turkey, November 1992, pp. 33-39.

  183. Oommen, B.J. and Zgierski, J., SEATER : A Simulation Environment Using Learning Automata for Telephone Traffic Routing, Proceedings of IEEE-SMC'92, the 1992 IEEE International Conference on Systems, Man and Cybernetics, Chicago, Illinois, October 1992, pp. 43-48.

  184. Valiveti, R.S. and Oommen, B.J., A Doubly-Linked List Reorganizing Strategy with Stochastic Move-to-End Operations, Proceedings of ICCCS'92, the 1992 International Conference of the Chilean Computer Science Society, Santiago, Chile, October 1992, pp. 249-257.

  185. Oommen, B.J. and Fothergill, C., The Image Examination and Retrieval Problem : A Learning Automaton-Based Solution, Proceedings of ICARCV'92, the 1992 International Conference on Automation, Robotics, and Computer Vision, Singapore, September 1992, pp. 21.5.1-21.5.5.

  186. Oommen, B.J. and Ng, D.T.H., Enhancing Data Retrieval Using Artificially Synthesized Queries, Proceedings of ORSA-CSTS'92, the 1992 ORSA-CSTS Conference on Computer Science and Operations Research : New Developments in Their Interfaces, Williamsburg, Virginia, January 1992, pp. 513-532.

  187. Valiveti, R.S. and Oommen, B.J., The Move-to-Front List Organizing Heuristic for Non-Stationary Query Distributions, Proceedings of ISCIS'91, the 1991 International Symposium on Computer and Information Sciences, Antalya, Turkey, October/November 1991, pp. 105-114.

  188. Valiveti, R.S. and Oommen, B.J., New Absorbing and Ergodic Doubly-Linked List Reorganizing Heuristics, Proceedings of ICCCS'91, the 1991 International Conference of the Chilean Computer Science Society, Santiago, Chile, October 1991, pp. 170-181.

  189. Lanctôt, J.K. and Oommen, B.J., On Discretizing Estimator-Based Learning Algorithms, Proceedings of IEEE-SMC'91, the 1991 IEEE International Conference on Systems, Man and Cybernetics, Charlottesville, Virginia, October 1991, pp. 1417-1422.

  190. Oommen, B.J , Ng, D.T.H. and Hansen, E.R., On Using Random Races in Learning Machines which Rank Actions in Stochastic Environments, Proceedings of IEEE-SMC'91, the 1991 IEEE International Conference on Systems, Man and Cybernetics, Charlottesville, Virginia, October 1991, pp. 1465-1471.

  191. Valiveti, R.S. and Oommen, B.J., On Measuring Presortedness in Ensembles of Data Sequences, Proceedings of AllertonCCCC'91, the 1991 Allerton Conference on Communication, Control and Computing, University of Illinois at Urbana-Champaign, Illinois, October 1991, pp. 518-523.

  192. Valiveti, R.S., Oommen, B.J. and Zgierski, J., Adaptive List Reorganization for a System Processing Set Queries, Proceedings of FCT'91, the 1991 Conference on the Fundamentals of Computation Theory, September 1991, Berlin, Germany, pp. 405-414.

  193. Oommen, B.J. and Floyd E.T., An Improved Algorithm for the Recognition of Noisy Subsequences, Proceedings of AIANN'91, the 1991 IASTED International Symposium on Artificial Intelligence Applications and Neural Networks, July 1991, Zurich, pp. 145-147.

  194. Valiveti, R.S. and Oommen, B.J., A Syntactic-Statistical Pattern Recognition Approach to Distinguishing Between Encryption Keys, Proceedings of AIANN'91, the 1991 IASTED International Symposium on Artificial Intelligence Applications and Neural Networks, July 1991, Zurich, Switzerland, pp. 122-124.

  195. Oommen, B.J. and Zgierski, J., On Breaking Substitution Cyphers Using Learning Automata, Proceedings of IEA/AIE'91, the 1991 IEA/AIE International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Hawaii, USA, June 1991, pp. 284-293.

  196. Oommen, B.J. and Zgierski, J., Keyboard Optimization Using Genetic Techniques, Proceedings of PCCC'91, the 1991 Phoenix Conference on Computers and Communications, Scottsdale, Arizona, March 1991, pp. 726-732.

  197. Valiveti, R.S. and Oommen, B.J., The Optimality of the Chi-Squared Metric for Determining Dependence in Normal Vectors, Proceedings of ISITA'90, the 1990 International Symposium on Information Theory and its Applications, November 1990, Hawaii, USA, pp. 375-378.

  198. Oommen, B.J., Object Partitioning Using a Hierarchy of Stochastic Automata, Proceedings of IEEE-SMC'90, the 1990 IEEE International Conference on Systems, Man and Cybernetics, Los Angeles, California, November 1990, pp. 184-187.

  199. Oommen, B.J., Valiveti, R.S. and Zgierski, J., A Fast Learning Automaton Solution to the Keyboard Optimization Problem, Proceedings of IEA/AIE'90, the 1990 IEA/AIE International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, Charleston, South Carolina, July 1990, pp. 981-990.

  200. Valiveti, R.S. and Oommen, B.J., On the Problem of Recognizing Sources Generating Random Strings, Proceedings of CISS'90, the 1990 Princeton Conference on Information Sciences and Systems, Princeton, New Jersey, March 1990, pp. 972-977.

  201. Christensen, J.P.R. and Oommen, B.J., On Using Distribution Theory to Prove the Epsilon-Optimality of Stubborn Learning Mechanisms, Proceedings of IEEE-SMC'89, the 1989 IEEE International Conference on Systems, Man and Cybernetics, Boston, Massachusetts, November 1989, pp. 286-291.

  202. Oommen, B.J. and Lanctôt, J.K., Epsilon-Optimal Discretized Pursuit Learning Automata, Proceedings of IEEE-SMC'89, the 1989 IEEE International Conference on Systems, Man and Cybernetics, November 1989, Boston, Massachusetts, pp. 6-12.

  203. Valiveti, R.S. and Oommen, B.J., A New Metric for Determining Dependence Trees for Pattern Recognition, Proceedings of ISCADSP'89, the 1989 IEE International Symposium on Computer Architecture and Digital Signal Processing, October 1989, Hong Kong, pp. 474-479.

  204. Ng, D.T.H. and Oommen, B.J., Generalizing Singly-Linked List Reorganizing Heuristics for Doubly-Linked Lists, Proceedings of MFCS'89, the 1989 Conference on the Mathematical Foundations of Computer Science, Rytro, Poland, Aug./Sept., 1989, pp. 380-389.

  205. Oommen, B, J. and Ng, D.T.H., Optimal Constant Space Move-To-Rear List Organization, Proceedings of ISOA'89, the 1989 International Symposium on Optimal Algorithms, Varna, Bulgaria, May /June 1989, pp. 115-125.

  206. Oommen, B, J. and Ng, D.T.H., Arbitrarily Distributed Random Permutation Generation, Proceedings of ACMSE'89, the 1989 ACM South Eastern Conference, Louisville, Kentucky, February 1989, pp. 27-32.

  207. Ng, D.T.H., Oommen, B.J. and Hansen, E.R., The Theory and Applications of Uni-Dimensional Random Races with Probabilistic Handicaps, Proceedings of ICACCS'88, the 1988 International Conference on Advances in Communications and Control Systems, Baton Rouge, Louisiana, October 1988, pp. 1228-1237.

  208. Cheetham, R.P., Oommen, B.J. and Ng, D.T.H., On Using Conditional Rotation Operations to Adaptively Structure Binary Search Trees, Proceedings of ICDT'88, the 1988 International Conference on Database Theory, Bruges, Belgium, August/September 1988, pp. 161-175.

  209. Oommen, B.J., Iyengar S.S. and Andrade, N., On Using Stochastic Automata for Trajectory Planning of Robot Manipulators in Noisy Workspaces, Proceedings of IEEE-CAIA'88, the 1988 IEEE Conference on Artificial Intelligence Applications, San Diego, California, March, 1988, pp. 88-94.

  210. Oommen, B.J. and Reichstein, I., On Batch Scheduled Multiple Mobile Robots Cluttering a Workspace, Proceedings of IEEE-CDC'87, the 1987 IEEE International Conference on Decision and Control, December 1987 Los Angeles, California, pp. 645-648.

  211. Oommen, B.J. and Christensen, J.P.R., On Three Families of Asymptotically Optimal Linear Reward-Penalty Learning Automata, Proceedings of IEEE-SMC'87, the 1987 IEEE International Conference on Systems, Man and Cybernetics, October 1987, Alexandria, Virginia, pp. 923-928.

  212. Oommen, B.J., Hansen, E.R. and Munro, J.I., Deterministic Move-to-Rear List Organizing Strategies with Optimal and Expedient Properties, Proceedings of AllertonCCCC'87, the 1987 Allerton Conference on Communication, Control and Computing, University of Illinois at Urbana-Champaign, Illinois, September/October 1987, pp. 54-63.

  213. Reichstein, I. and Oommen, B.J., On List Scheduled Multiple Mobile Robots Cluttering a Workspace, Proceedings of ISRA'87, the 1987 IASTED International Symposium on Robotics and Automation, June 1987, Lugano, Switzerland, pp. 65-69.

  214. Oommen, B.J. and Ma, D.C.Y., Fast Object Partitioning Using Stochastic Learning Automata, Proceedings of ICRDIR'87, the 1987 International Conference on Research and Development in Information Retrieval, New Orleans, Louisiana, June 1987, pp. 111-122.

  215. Reichstein, I. and Oommen, B.J., Computational Issues in determining the Optimal Number of Mobile Robots Operating in a Common Workspace, Proceedings of PCMS'87, the 1987 Pittsburgh Conference on Modeling and Simulation, Pittsburgh, Pennsylvania, Vol. 18, April 1987, pp. 845-854.

  216. Oommen, B.J., The Noisy Subsequence Recognition Problem, Proceedings of CISS'87, the 1987 Conference on Information Sciences and Systems, Johns Hopkins University, Maryland, Vol. 21, March 1987, pp. 752-758.

  217. Rao, S.V.N., Iyengar, S.S., Oommen, B.J. and Kashyap, R.L., Terrain Acquisition by Point Robot Amidst Polyhedral Obstacles, Proceedings of IEEE-ICAIA'87, the 1987 IEEE International Conference on Artificial Intelligence Applications, Kissimmee, Florida, Feb. 1987, pp. 170-175.

  218. Oommen, B.J. and Ma, D.C.Y., Fast Automata Solutions to the Equal Partitioning Problem, Proceedings of IEEE-COMPSAC'86, the 1986 IEEE Computer Software and Applications Conference, Chicago, Illinois, October 1986, pp. 358-364.

  219. Oommen, B.J., On How Two-Action Ergodic Learning Automata Can Utilize A priori Information, Proceedings of IEEE-SMC'86, the 1986 IEEE International Conference on Systems, Man and Cybernetics, October 1986, Atlanta, Georgia, pp. 308-312.

  220. Oommen, B.J. and Hansen, E.R., Expedient Stochastic Move-to-Front and Optimal Stochastic Move-to-Rear List Organizing Strategies, Proceedings of ICDT'86, the 1986 International Conference on Database Theory, Rome, Italy, September 1986, pp. OH-1-16.

  221. Oommen, B.J., Iyengar, S.S., Rao, S.V.N. and Kashyap, R.L., Robot Navigation in Unknown Terrains of Convex Polygonal Obstacles Using Learned Visibility Graphs, Proceedings of NCAI'86, the 1986 National Conference on Artificial Intelligence, Philadelphia, Pennsylvania, August 1986, pp. 1101-1106.

  222. Oommen, B.J. and Reichstein, I.R., On Translating Ellipses Amidst Elliptic Obstacles, Proceedings of IEEE-RA'86, the 1986 IEEE International Conference on Robotics and Automation, San Francisco, California, April 1986, pp. 1755-1760.

  223. Oommen, B.J., On the Futility of Arbitrarily Increasing the Memory Capabilities of Stochastic Learning Automata, Proceedings of IEEE-ICAIA'86, the 1986 IEEE International Conference on Artificial Intelligence Applications, Miami Beach, Florida, December 1985, pp. 308-312.

  224. Oommen, B.J., Linear and Nonlinear Absorbing and Ergodic Discretized Two Action Learning Automata, Proceedings of IEEE-SMC'85, the 1985 IEEE International Conference on Systems, Man and Cybernetics, Tucson, Arizona, November 1985, pp. 241-245.

  225. Oommen, B.J., A Possibly Linear Minimum Spanning Circle Algorithm, Proceedings of AllertonCCCC'85, the 1985 Allerton Conference on Communication, Control and Computing, University of Illinois at Urbana-Champaign, Illinois, October 1985, pp. 506-507.

  226. Oommen, B.J. and Hansen, E.R., The Asymptotic Properties of Two Action Discretized Linear Inaction-Penalty Learning Automata, Proceedings of CISS'85, the 1985 Conference on Information Sciences and Systems, Johns Hopkins University, Maryland, March 1985, pp. 647-653.

  227. Oommen, B.J., On the Use of Smoothsort and Stochastic Move-to-Front Operations for Optimal List Organization, Proceedings of AllertonCCCC'84, the 1984 Allerton Conference on Communication, Control and Computing, University of Illinois at Urbana-Champaign, Illinois, October 1984, pp. 243-252.

  228. Oommen, B.J., Algorithms for String Editing which Permit Arbitrarily Complex Edit Constraints, Proceedings of MFCS'84, the 1984 Conference on the Mathematical Foundations of Computer Science, Prague, Czechoslovakia, September, 1984, pp. 443-451.

  229. Oommen, B.J., The Applicability of Generalized Krylov Automata to Learning in Non-stationary Environments, Proceedings of PCMS'84, the 1984 Pittsburgh Conference on Modeling and Simulation, Pittsburgh, Pennsylvania, April 1984, pp. 789-798.

  230. Oommen, B.J. and Hansen, E.R., The Optimal Properties of Two Action Discretized Reward-Inaction Learning Automata, Proceedings of CISS'84, the 1984 Princeton Conference on Information Sciences and Systems, Princeton, New Jersey, March 1984, pp. 658-662.

  231. Oommen, B.J. and Kashyap, R.L., A Scale Preserving Cartographic Smoothing Technique for Islands and Lakes, Proceedings of AutoCarto'83: The 1983 International Symposium on Automated Cartography, Ottawa, Canada, October 1983, pp. 243-251.

  232. Oommen, B.J. and Thathachar, M.A.L., Multi-action Learning Automata Possessing Ergodicity of the Mean, Proceedings of MECO'83: The 1983 IASTED International Symposium on Measurement and Control, Athens, Greece, August 1983, pp. 61-64.

  233. Thathachar, M.A.L. and Oommen, B.J., Generalized Krylov Automata, Proceedings of CISS'83, the 1983 Conference on Information Sciences and Systems, Johns Hopkins University, Maryland, March 1983, pp. 495-500.

  234. Thathachar, M.A.L. and Oommen, B.J., Two Action Learning Automata Possessing Ergodicity of the Mean, Proceedings of PCCC'83, the 1983 Phoenix Conference on Computers and Communications, Phoenix, Arizona, March 1983, pp. 252-256.

  235. Kashyap, R.L. and Oommen, B.J., A Geometrical Approach to Polygonal Dissimilarity and the Classification of Closed Boundaries, Proceedings of ICPR'82, the 1982 International Conference on Pattern Recognition, Munich, Germany, October 1982, pp. 472-479.

  236. Kashyap, R.L. and Oommen, B.J., Probabilistic Correction of Strings, Proceedings of PRIP'82, the 1982 IEEE Conference in Pattern Recognition and Image Processing, Las Vegas, Nevada, June 1982, pp. 28-33.

  237. Kashyap, R.L. and Oommen, B.J., Similarity and Dissimilarity Measures for Sets of Strings, Proceedings of CISS'82, the 1982 Princeton Conference on Information Sciences and Systems, Princeton, New Jersey, March 1982, pp. 101-105.

  238. Kashyap, R.L. and Oommen, B.J., Pattern Matching with Noisy Substrings, Proceedings of IEEE-COMPSAC'80, the 1980 IEEE Computer Software and Application Conference, Chicago, Illinois, November 1981, pp. 119-125.

  239. Kashyap, R.L. and Oommen, B.J., A Unifying Theory for Order Preserving Properties Involving Two Strings, Proceedings of CISS'80, the 1980 Princeton Conference on Information Sciences and Systems, Princeton, New Jersey, March 1980, pp. 193-198.

  240. Kashyap, R.L. and Oommen, B.J., An Effective Algorithm for String Correction Using a Generalized Distance, Proceedings of IEEE-PRIP'79, the 1979 IEEE Computer Society Conference on Pattern Recognition and Image Processing, Chicago, Illinois, August 1979, pp. 184-191.

BOOK CHAPTERS

  1. Emerging Trends in Machine Learning: Classification of Stochastically Episodic Events. In Emerging Paradigms in Machine Learning and Applications, pp. 161-195. Published by Springer (Series: Smart Innovation, Systems and Technologies). Edited by S. Ramanna, R. J. Howett and L. Jain. (Co-authored by C. Bellinger), 2012.

  2. Fault-Tolerant Routing in Mobile Ad Hoc Networks. In Theory and Applications of Ad Hoc Networks, pp. 323-344. Published by INTECH. Edited by W. Xin. (Co-authored by L. Rueda), 2011.

  3. An Enhanced Tree-shaped Adachi-like Chaotic Neural Network Requiring Linear-time Computations. In Chaotic Systems: Theory and Applications, pp. 284-293. Published by World Scientific. Edited by C. H. Skiadas and I. Dimotikalis. (Co-authored by K. Qin), 2010.

  4. Stochastic Learning-based Weak Estimation and Its Applications. In Knowledge-based Intelligent System Advancements: Systemic and Cybernetic Approaches, pp. 1-29. Published by Published by IGI Global in the Advances in Artificial Intelligence Technologies series. Edited by J. Jozefczyk and D. Orski. ISBN: 978-1-61692-811-7. (Co-authored by L. Rueda), 2010.

  5. Learning Automata-based Solutions to Stochastic Nonlinear Resource Allocation Problems. In Intelligent Systems for Knowledge Management, SCI 252, pp. 1-30. Published by Springer Publishers. Edited by N. T. Nguyen and E. Szczerbicki. (Co-authored by O-C. Granmo), 2009.

  6. Learning Automata-based Solutions to the Goore Game and its Applications. In Game Theory: Strategies, Equilibria, and Theorems, pp. 183-216. Published by Nova Science Publishers, New York. Edited by Edited by I. N. Haugen and A. S. Nilsen. (Co-authored by O-C. Granmo), 2009.

  7. Cybernetics and Learning Automata. In Handbook of Automation, pp. 219-232, 2009. Published by Springer Publishers, New York. Edited by S. Y. Nof. (Co-authored by S. Misra).

  8. On Enhancing Query Optimization in the ORACLE Database System by Utilizing Attribute Cardinality Maps. In Enterprise Information Systems VIII, pp. 38-71, 2008. Published by Springer as LNBIP - the Lecture Notes in Business Information Processing. Vol. 3. Edited by Y. Manolopoulos, J. Filipe, P. Constantopoulos and J. Cordeiro. ISBN: 978-3-540-77580-5. (Co-authored by J. Chen).

  9. Introduction to Chaotic Pattern Recognition: Periodicity and Stability Issues of a Chaotic Neural Network. In Pattern Recognition Theory and Application, pp. 239- 257, 2008. Published by Nova Science Publishers, New York. Edited by Erwin A. Zoeller. (Co-authored by D. Calitoiu and D. Nussbaum).

  10. String Correction Using Probabilistic Methods. In Computer Text Recognition and Error Correction. Published by the IEEE Computer Society. Edited by S. N. Srihari. (Co-authored by R.L. Kashyap).

  11. The Noisy Substring Matching Problem. In Computer Algorithms : String Pattern Matching Strategies. Published by the IEEE Computer Society. Edited by J-I. Aoe. (Co-authored by R.L. Kashyap).

PAPERS TO BE SUBMITTED (A SHORT LIST)
  1. Valiveti, R.S. and Oommen, B.J., Adaptive List Organizing for Non-Stationary Query Distributions. Part I : The Move-to-Front Rule. (Being Revised).

  2. Valiveti, R.S. and Oommen, B.J., On Evaluating Learning Organisms and Mechanisms in a Generalized Learning Paradigm. (Being Revised).

  3. Oommen, B.J. and Loke, R., Noisy Subsequence Recognition Using Constrained String Editing Involving Arbitrary Operations. (Being Revised).

  4. Oommen, B.J. and Dong, J., On the Time Reversibility of a Well Known Self-Organizing Sequential Search Algorithm. (Being Revised).

  5. Oommen, B.J. and Dong, J., The Swap-with-Parent Scheme: A Self -Organizing Sequential Search Algorithm which Uses Non-lexicographic Heaps. (Being Revised).

  6. Oommen, B.J. and Dong, J., Time Reversibility: A Mathematical Tool for Creating Arbitrary Generalized Swap-with-Parent Self-Organizing Lists. (Being Revised).

  7. Oommen, B.J. and Roberts, T.D., Learning Automata Solutions to the Capacity Assignment with Priority Assignment Problem. (In Preparation).

  8. Oommen, B.J. and Loke, R. K. S., A Formal Theory for Optimal and Information Theoretic Syntactic Pattern Recognition for Traditional and Generalized Transposition Errors. (In Preparation).

  9. Dong, J. and Oommen, B.J., Some Enumeration Results on Complete k-ary Trees. (In Preparation).

  10. Oommen, B. J., Matwin, S. and Ouerd, M., Algorithms for Building Bayesian Polytree Structures using Data Distributions. (In Preparation).

PATENTS

  1. Search-Enhanced Trie-Based Syntactic Pattern Recognition of Sequences. Inventors: Ghada Badr and B. John Oommen. U.S. and Canada. U.S Patent No. 7,689,588 issued on March 30, 2010. Canadian Patent No. 2,608,772 issued on March 22, 2013. Click here for an overview.

  2. Significance of the Patent: This patent solves the problem of achieving the syntactic pattern recognition of sequences, when the dictionary is stored as a trie. The competing patent was invented by Risvik, and our invention is, in some cases, five times faster than Risvik's.

  3. A Method For Encryption with Statistical Perfect Secrecy. Inventors: B. John Oommen and Luis G. Rueda. U.S., Canada, and in some other countries. U.S. Patent No. 7,508,935 issued on March 24, 2009. Canadian Patent No. 2,460,863 issued on April 26, 2011. Click here for an overview.

  4. To view the results of the FIPS-140-2 tests and other statistical tests on files encrypted with this encryption Click here .

    Significance of the Patent: This patent solves a compression-based problem that was reported to be unsolved in the standard textbooks. Using this solution, we were able to invent an encryption which provided Statistical Perfect Secrecy. We believe that our solution is still the only one known for this problem.

  5. Method of Comparing the Closeness of a Target Tree to Other Trees Using Noisy Subsequence Tree Processing. Inventor: B. John Oommen. U.S. and Canada. U.S. Patent No. 7,278,026 issued on October 23, 2007. Canadian Patent No. 2,386,578 issued on June 8, 2010. For an overview click here. For information on Drug Design click here, or find more information here.

  6. Significance of the Patent: This patent solves the problem of recognizing noisy subsequence trees. To the best of our knowledge, our patented solution is still the only patented invention which solves the problem.

  7. A Method of Generating Attribute Cardinality Maps. Inventor: B. John Oommen and Murali Thiyagarajah. U.S. and Canada. U.S Patent No. 6,865,567 issued on March 8, 2005. Canadian Patent No. 2,279,359 issued on March 16, 2012. For an overview click here.

  8. Significance of the Patent: All the database systems (ORACLE, DB2, Sybase etc.) achieve query optimization using the equi-depth histogram. This patent presents two new histogram methods, namely the Rectangular Attribute Cardinality Map and the Trapezoidal Attribute Cardinality Map. Both of these estimate the query result sizes more accurately than the equi-depth histogram, and thus yield significantly superior query optimization.
INVITED TALKS & SEMINARS

    I have presented seminars at various universities and research centers in Argentina, Australia, Canada, Chile, Denmark, France, Holland, Hong Kong, India, Japan, Korea, Norway, Singapore, Spain, Turkey, the USA etc.
Home | Personal | Education | Work | Research | Publications | Students | Search