| 2022 | FlAIRS | Learning Automata with Artificial Reflecting Barriers in Games with Limited Information. | Ismail Hassan, B. John Oommen, Anis Yazidi |
| 2019 | EANN | The Power of the "Pursuit" Learning Paradigm in the Partitioning of Data. | Abdolreza Shirvani, B. John Oommen |
| 2017 | ADMA | A Higher-Fidelity Frugal Quantile Estimator. | Anis Yazidi, Hugo Lewi Hammer, B. John Oommen |
| 2017 | ADMA | Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments. | Anis Yazidi, B. John Oommen, Morten Goodwin |
| 2017 | CEC | On using novel "Anti-Bayesian" techniques for the classification of dynamical data streams. | Hugo Lewi Hammer, Anis Yazidi, B. John Oommen |
| 2016 | ICCCI | On the Foundations of Multinomial Sequence Based Estimation. | B. John Oommen, Sang-Woon Kim |
| 2015 | ICCCI | Text Classification Using Novel "Anti-Bayesian" Techniques. | B. John Oommen, Richard Khoury, Aron Schmidt |
| 2015 | ICCCI | Enhancing History-Based Move Ordering in Game Playing Using Adaptive Data Structures. | Spencer Polk, B. John Oommen |
| 2014 | PRICAI | Fast BMU Search in SOMs Using Random Hyperplane Trees. | Csar A. Astudillo, B. John Oommen |
| 2013 | CAIP | A Novel Border Identification Algorithm Based on an "Anti-Bayesian" Paradigm. | Anu Thomas, B. John Oommen |
| 2013 | CAIP | On Achieving Near-Optimal "Anti-Bayesian" Order Statistics-Based Classification for Asymmetric Exponential Distributions. | Anu Thomas, B. John Oommen |
| 2013 | PIMRC | Channel selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata approach. | Xuan Zhang, Lei Jiao, Ole-Christoffer Granmo, B. John Oommen |
| 2013 | SGAI | On Applying Adaptive Data Structures to Multi-Player Game Playing. | Spencer Polk, B. John Oommen |
| 2012 | CIARP | Optimal "Anti-Bayesian" Parametric Pattern Classification Using Order Statistics Criteria. | Anu Thomas, B. John Oommen |
| 2012 | DCAI | A Fast Heuristic Solution for the Commons Game. | Rokhsareh Sakhravi, Masoud T. Omran, B. John Oommen |
| 2011 | ACIIDS | A New Frontier in Novelty Detection: Pattern Recognition of Stochastically Episodic Events. | Colin Bellinger, B. John Oommen |
| 2011 | HAIS | Using Artificial Intelligence Techniques for Strategy Generation in the | Petro Verkhogliad, B. John Oommen |
| 2011 | HAIS | A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes. | Anis Yazidi, Ole-Christoffer Granmo, B. John Oommen |
| 2011 | ISI | Anomaly detection using weak estimators. | Justin Zhan, B. John Oommen, Johanna Crisostomo |
| 2010 | AI | Potential AI Strategies to Solve the | Petro Verkhogliad, B. John Oommen |
| 2010 | ICAART | On using Simulation and Stochastic Learning for Pattern Recognition When Training Data is Unavailable - The Case of Disease Outbreak. | Dragos Calitoiu, B. John Oommen |
| 2010 | ICAART | A Generic Solution to Multi-Armed Bernoulli Bandit Problems based on Random Sampling from Sibling Conjugate Priors. | Thomas Norheim, Terje Brdland, Ole-Christoffer Granmo, B. John Oommen |
| 2010 | PRICAI | Learning Automaton Based On-Line Discovery and Tracking of Spatio-temporal Event Patterns. | Anis Yazidi, Ole-Christoffer Granmo, Min Lin, Xifeng Wen, B. John Oommen, Martin Gerdes, Frank Reichert |
| 2010 | SSPR | Language Detection and Tracking in Multilingual Documents Using Weak Estimators. | Aleksander Stensby, B. John Oommen, Ole-Christoffer Granmo |
| 2009 | AICCSA | An adaptive learning-like solution of random early detection for congestion avoidance in computer networks. | Sudip Misra, B. John Oommen, Sreekeerthy Yanamandra, Mohammad S. Obaidat |
| 2009 | KES | Learning Automata Based Intelligent Tutorial- | B. John Oommen, M. Khaled Hashem |
| 2008 | ACISP | Enhancing Micro-Aggregation Technique by Utilizing Dependence-Based Information in Secure Statistical Databases. | B. John Oommen, Ebaa Fayyoumi |
| 2008 | AI | A Fast Computation of Inter-class Overlap Measures Using Prototype Reduction Schemes. | Sang-Woon Kim, B. John Oommen |
| 2008 | CIARP | Chernoff-Based Multi-class Pairwise Linear Dimensionality Reduction. | Luis Rueda, Claudio Henrquez, B. John Oommen |
| 2008 | SSPR | Chaotic Pattern Recognition: The Spectrum of Properties of the Adachi Neural Network. | Ke Qin, B. John Oommen |
| 2007 | AI | Analytic Results on the Hodgkin-Huxley Neural Network: Spikes Annihilation. | Dragos Calitoiu, B. John Oommen, Doron Nussbaum |
| 2007 | AINA | The Pursuit Automaton Approach for Estimating All-Pairs Shortest Paths in Dynamically Changing Networks. | Sudip Misra, B. John Oommen |
| 2007 | ICICS | A Novel Method for Micro-Aggregation in Secure Statistical Databases Using Association and Interaction. | B. John Oommen, Ebaa Fayyoumi |
| 2007 | SMC | Using learning automata to model the behavior of a teacher in a tutorial-like system. | M. Khaled Hashem, B. John Oommen |
| 2007 | SMC | Using learning automata to model a student-classroom interaction in a tutorial-like system. | M. Khaled Hashem, B. John Oommen |
| 2006 | ACISP | On Optimizing the | Ebaa Fayyoumi, B. John Oommen |
| 2006 | INFOCOM | A Stochastic Random-Races Algorithm for Routing in MPLS Traffic Engineering. | B. John Oommen, Sudip Misra, Ole-Christoffer Granmo |
| 2006 | PSD | A Fixed Structure Learning Automaton Micro-aggregation Technique for Secure Statistical Databases. | Ebaa Fayyoumi, B. John Oommen |
| 2006 | SMC | An Application of a Game of Discrete Generalised Pursuit Automata to Solve a Multi-Constraint Partitioning Problem. | Geir Horn, B. John Oommen |
| 2006 | WiMob | A Fault-Tolerant Routing Algorithm for Mobile Ad Hoc Networks Using a Stochastic Learning-Based Weak Estimation Procedure. | B. John Oommen, Sudip Misra |
| 2006 | SSPR | On Optimizing Kernel-Based Fisher Discriminant Analysis Using Prototype Reduction Schemes. | Sang-Woon Kim, B. John Oommen |
| 2006 | SSPR | On the Theory and Applications of Sequence Based Estimation of Independent Binomial Random Variables. | B. John Oommen, Sang-Woon Kim, Geir Horn |
| 2005 | ISCC | New Algorithms for Maintaining All-Pairs Shortest Paths. | Sudip Misra, B. John Oommen |
| 2005 | KI | On Utilizing Stochastic Learning Weak Estimators for Training and Classification of Patterns with Non-stationary Distributions. | B. John Oommen, Lus G. Rueda |
| 2004 | AAAI | Adaptive Algorithms for Routing and Traffic Engineering in Stochastic Networks. | Sudip Misra, B. John Oommen |
| 2004 | ISCC | Generalized pursuit learning algorithms for shortest path routing tree computation. | Sudip Misra, B. John Oommen |
| 2004 | SSPR | Dictionary-Based Syntactic Pattern Recognition Using Tries. | B. John Oommen, Ghada Badr |
| 2004 | SSPR | A New Family of Weak Estimators for Training in Non-stationary Distributions. | B. John Oommen, Lus G. Rueda |
| 2003 | AI | Enhancing Caching in Distributed Databases Using Intelligent Polytree Representations. | Ouerd Messaouda, B. John Oommen, Stan Matwin |
| 2002 | SMC | Creative prototype reduction schemes: a taxonomy and ranking. | Sang-Woon Kim, B. John Oommen |
| 2002 | SMC | Data generation for testing DAG-structured Bayesian networks. | Ouerd Messaouda, B. John Oommen, Stan Matwin |
| 2002 | SSPR | Recursive Prototype Reduction Schemes Applicable for Large Data Sets. | Sang-Woon Kim, B. John Oommen |
| 2001 | DASFAA | Histogram Methods in Query Optimization: The Relation between Accuracy and Optimality. | B. John Oommen, Lus G. Rueda |
| 2001 | SMC | Enhanced static Fano coding. | Lus G. Rueda, B. John Oommen |
| 2000 | ECAI | A Kohonen-like Decomposition Method for the Traveling Salesman Problem: KNIES | Necati Aras, I. Kuban Altinel, B. John Oommen |
| 2000 | IDEAS | Query Result Size Estimation Using the Trapezoidal Attribute Cardinality Map. | B. John Oommen, Murali Thiyagarajah |
| 2000 | ISMIS | A Formalism for Building Causal Polytree Structures Using Data Distributions. | M. Ouerd, B. John Oommen, Stan Matwin |
| 2000 | SSPR | The Foundational Theory of Optimal Bayesian Pairwise Linear Classifiers. | Luis Rueda, B. John Oommen |
| 1999 | DEXA | On Benchmarking Attribute Cardinality Maps for Database Systems Using the TPC-D Specification. | Murali Thiyagarajah, B. John Oommen |
| 1999 | IDEAS | Query Result Size Estimation Using a Novel Histogram-like Technique: The Rectangular Attribute Cardinality Map. | B. John Oommen, Murali Thiyagarajah |
| 1998 | SSPR | The Noisy Subsequence Tree Recognition Problem. | B. John Oommen, R. K. S. Loke |
| 1997 | ISAAC | Generalized Swap-with-Parent Schemes for Self-Organizing Sequential Linear Lists. | B. John Oommen, Juan Dong |
| 1996 | ICPR | Probabilistic syntactic pattern recognition for traditional and generalized transposition errors. | B. John Oommen, Richard K. S. Loke |
| 1996 | SSPR | Optimal and Information Theoretic Syntactic Pattern Recognition for Traditional Errors. | B. John Oommen, Rangasami L. Kashyap |
| 1995 | LATIN | On Using Learning Automata for Fast Graph Partitioning. | B. John Oommen, Edward V. de St. Croix |
| 1991 | FCT | Adaptive Linear List Reorganization for a System Processing Set Queries. | Radhakrishna S. Valiveti, B. John Oommen, Jack R. Zgierski |
| 1989 | MFCS | Generalizing Singly-Linked List Reorganizing Heuristics for Doubly-Linked Lists. | David T. H. Ng, B. John Oommen |
| 1989 | SMC | On using distribution theory to prove the epsilon-optimality of stubborn learning mechanisms. | Jens Peter Reus Christensen, B. John Oommen |
| 1989 | SMC | Epsilon-optimal discretized pursuit learning automata. | B. John Oommen, J. Kevin Lanctt |
| 1988 | ICDT | On Using Conditional Rotation Operations to Adaptively Structure Binary Search Trees. | Robert P. Cheetham, B. John Oommen, David T. H. Ng |
| 1987 | SIGIR | Fast Object Partitioning Using Stochastic Learning Automata. | B. John Oommen, Daniel C. Y. Ma |
| 1986 | AAAI | Robot Navigation in Unknown Terrains of Convex Polygonal Obstacles Using Learned Visibility Graphs. | B. John Oommen, S. Sitharama Iyengar, Nageswara S. V. Rao, Rangasami L. Kashyap |
| 1986 | ICDT | Expedient Stochastic Move-to-Front and optimal Move-to-Rear List Organizing Strategies. | B. John Oommen, E. R. Hansen |
| 1986 | ICRA | On translating ellipses amidst elliptic obstacles. | B. John Oommen, Irwin Reichstein |
| 1984 | MFCS | Algorithms for String Editing which Permit Arbitrarily Complex Editing Constraints. | B. John Oommen |