An effective algorithm for string correction using generalized edit distances–I. Description of the algorithm and its optimality. - Rangasami L. Kashyap; B. John Oommen (Inf. Sci., 1981)

An effective algorithm for string correction using generalized edit distance - II. Computational complexity of the algorithm and some applications. - Rangasami L. Kashyap; B. John Oommen (Inf. Sci., 1981)

A Geometrical Approach to Polygonal Dissimilarity and Shape Matching. - Rangasami L. Kashyap; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 1982)

Scale Preserving Smoothing of Polygons. - Rangasami L. Kashyap; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 1983)

The Noisy Substring Matching Problem. - Rangasami L. Kashyap; B. John Oommen (IEEE Trans. Software Eng., 1983)

Learning automata processing ergodicity of the mean: The two-action case. - M. A. L. Thathachar 001; B. John Oommen (IEEE Trans. Syst. Man Cybern., 1983)

Algorithms for String Editing which Permit Arbitrarily Complex Editing Constraints. - B. John Oommen (MFCS, 1984)

Spelling correction using probabilistic methods. - Rangasami L. Kashyap; B. John Oommen (Pattern Recognit. Lett., 1984)

The asymptotic optimality of discretized linear reward-inaction learning automata. - B. John Oommen; E. R. Hansen (IEEE Trans. Syst. Man Cybern., 1984)

On the Futility of Arbitrarily Increasing Memory Capabilities of Stochastic Learning Automata. - B. John Oommen (CAIA, 1985)

Multiaction learning automata possessing ergodicity of the mean. - B. John Oommen; M. A. L. Thathachar 001 (Inf. Sci., 1985)

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 (AAAI, 1986)

Expedient Stochastic Move-to-Front and optimal Move-to-Rear List Organizing Strategies. - B. John Oommen; E. R. Hansen (ICDT, 1986)

On translating ellipses amidst elliptic obstacles. - B. John Oommen; Irwin Reichstein (ICRA, 1986)

Constrained string editing. - B. John Oommen (Inf. Sci., 1986)

Absorbing and Ergodic Discretized Two-Action Learning Automata. - B. John Oommen (IEEE Trans. Syst. Man Cybern., 1986)

A Learning Automaton Solution to the Stochastic Minimum-Spanning Circle Problem. - B. John Oommen (IEEE Trans. Syst. Man Cybern., 1986)

Fast Object Partitioning Using Stochastic Learning Automata. - B. John Oommen; Daniel C. Y. Ma (SIGIR, 1987)

An Efficient Geometric Solution to the Minimum Spanning Circle Problem. - B. John Oommen (Oper. Res., 1987)

Recognition of Noisy Subsequences Using Constrained Edit Distances. - B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 1987)

On the problem of translating an elliptic object through a workspace of elliptic obstacles. - B. John Oommen; Irwin Reichstein (Robotica, 1987)

List Organizing Strategies Using Stochastic Move-to-Front and Stochastic Move-to-Rear Operations. - B. John Oommen; E. R. Hansen (SIAM J. Comput., 1987)

Robot navigation in unknown terrains using learned visibility graphs. Part I: The disjoint convex obstacle case. - B. John Oommen; S. Sitharama Iyengar; Nageswara S. V. Rao; Rangasami L. Kashyap (IEEE J. Robotics Autom., 1987)

Ergodic Learning Automata Capable of Incorporating a Priori Information. - B. John Oommen (IEEE Trans. Syst. Man Cybern., 1987)

On Using Conditional Rotation Operations to Adaptively Structure Binary Search Trees. - Robert P. Cheetham; B. John Oommen; David T. H. Ng (ICDT, 1988)

Correction to "Recognition of Noisy Subsequences Using Constrained Edit Distances". - B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 1988)

Deterministic Learning Automata Solutions to the Equipartitioning Problem. - B. John Oommen; Daniel C. Y. Ma (IEEE Trans. Computers, 1988)

On terrain acquisition by a point robot amidst polyhedral obstacles. - Nageswara S. V. Rao; S. Sitharama Iyengar; B. John Oommen; Rangasami L. Kashyap (IEEE J. Robotics Autom., 1988)

ϵ-optimal discretized linear reward-penalty learning automata. - B. John Oommen; Jens Peter Reus Christensen (IEEE Trans. Syst. Man Cybern., 1988)

Generalizing Singly-Linked List Reorganizing Heuristics for Doubly-Linked Lists. - David T. H. Ng; B. John Oommen (MFCS, 1989)

Optimal Constant Space Move-to-Rear List Organization. - B. John Oommen; David T. H. Ng (Optimal Algorithms, 1989)

On using distribution theory to prove the epsilon-optimality of stubborn learning mechanisms. - Jens Peter Reus Christensen; B. John Oommen (SMC, 1989)

Epsilon-optimal discretized pursuit learning automata. - B. John Oommen; J. Kevin Lanctôt (SMC, 1989)

A Fast Learning Automaton Solution to the Keyboard Optimization Problem. - B. John Oommen; Radhakrishna S. Valiveti; Jack R. Zgierski (IEA/AIE (Vol. 2), 1990)

On Generating Random Permutations with Arbitrary Distributions. - B. John Oommen; David T. H. Ng (Comput. J., 1990)

Deterministic Optimal and Expedient Move-to-Rear List Organizing Strategies. - B. John Oommen; E. R. Hansen; J. Ian Munro (Theor. Comput. Sci., 1990)

Epsilon-optimal stubborn learning mechanisms. - Jens Peter Reus Christensen; B. John Oommen (IEEE Trans. Syst. Man Cybern., 1990)

Discretized pursuit learning automata. - B. John Oommen; J. Kevin Lanctôt (IEEE Trans. Syst. Man Cybern., 1990)

Adaptive Linear List Reorganization for a System Processing Set Queries. - Radhakrishna S. Valiveti; B. John Oommen; Jack R. Zgierski (FCT, 1991)

Stochastic Automata Solutions to the Object Partitioning Problem. - B. John Oommen; Daniel C. Y. Ma (Comput. J., 1991)

Trajectory Planning of Robot Manipulators in Noisy Work Spaces Using Stochastic Automata. - B. John Oommen; Nicte Andrade; S. Sitharama Iyengar (Int. J. Robotics Res., 1991)

Recognizing Sources of Random Strings. - Radhakrishna S. Valiveti; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 1991)

An adaptive learning solution to the keyboard optimization problem. - B. John Oommen; Radhakrishna S. Valiveti; Jack R. Zgierski (IEEE Trans. Syst. Man Cybern., 1991)

Enhancing Data Retrieval using Artificially synthesized Queries. - B. John Oommen; David T. H. Ng (Computer Science and Operations Research, 1992)

A Short Note on Doubly-Linked List Reorganizing Heuristics. - David T. H. Ng; B. John Oommen (Comput. J., 1992)

On the problem of multiple mobile robots cluttering a workspace. - B. John Oommen; Irwin Reichstein (Inf. Sci., 1992)

On using the chi-squared metric for determining stochastic dependence. - Radhakrishna S. Valiveti; B. John Oommen (Pattern Recognit., 1992)

Discretized estimator learning automata. - J. Kevin Lanctôt; B. John Oommen (IEEE Trans. Syst. Man Cybern., 1992)

Transforming Ill-Conditioned Constrained Problems using Projections. - B. John Oommen (Comput. J., 1993)

Fast Learning Automaton-Based Image Examination and Retrieval. - B. John Oommen; Chris Fothergill (Comput. J., 1993)

Self-Organizing Doubly-Linked Lists. - Radhakrishna S. Valiveti; B. John Oommen (J. Algorithms, 1993)

Breaking Substitution Cyphers Using Stochastic Automata. - B. John Oommen; Jack R. Zgierski (IEEE Trans. Pattern Anal. Mach. Intell., 1993)

Determining stochastic dependence for normally distributed vectors using the chi-squared metric. - Radhakrishna S. Valiveti; B. John Oommen (Pattern Recognit., 1993)

An Optimal Absorbing List Organization Strategy with Constant Memory Requirements. - B. John Oommen; David T. H. Ng (Theor. Comput. Sci., 1993)

Adaptive Structuring of Binary Search Trees Using Conditional Rotations. - Robert P. Cheetham; B. John Oommen; David T. H. Ng (IEEE Trans. Knowl. Data Eng., 1993)

Adaptive learning mechanisms for ordering actions using random races. - David T. H. Ng; B. John Oommen; E. R. Hansen (IEEE Trans. Syst. Man Cybern., 1993)

A New Technique for Enhancing Linked-List Data Retrieval: Reorganize Data Using Artificially synthesized Queries. - B. John Oommen; David T. H. Ng (Comput. J., 1994)

Constrained Tree Editing. - B. John Oommen; William Lee (Inf. Sci., 1994)

SEATER: An Object-Oriented Simulation Environment Using Learning Automata for Telephone Traffic Routing. - Jack R. Zgierski; B. John Oommen (IEEE Trans. Syst. Man Cybern. Syst., 1994)

Arbitrary distance function estimation using vector quantization. - B. John Oommen; I. Kuban Altinel; Necati Aras (ICNN, 1995)

Noisy Subsequence Recognition Using Constrained String Editing Involving Substitutions, Insertions, Deletions and Generalized Transpositions. - B. John Oommen; R. K. S. Loke (ICSC, 1995)

On Using Learning Automata for Fast Graph Partitioning. - B. John Oommen; Edward V. de St. Croix (LATIN, 1995)

String Alignment with Substitution, Insertion, Deletion, Squashing and Expansion Operations. - B. John Oommen (Inf. Sci., 1995)

Switching models for nonstationary random environments. - B. John Oommen; Hassan Masum (IEEE Trans. Syst. Man Cybern., 1995)

Mixture decomposition for distributions from the exponential family using a generalized method of moments. - S. T. Sum; B. John Oommen (IEEE Trans. Syst. Man Cybern., 1995)

Optimal and Information Theoretic Syntactic Pattern Recognition Involving Traditional and Transposition Errors. - B. John Oommen; R. K. S. Loke (FSTTCS, 1996)

Probabilistic syntactic pattern recognition for traditional and generalized transposition errors. - B. John Oommen; Richard K. S. Loke (ICPR, 1996)

Optimal and Information Theoretic Syntactic Pattern Recognition for Traditional Errors. - B. John Oommen; Rangasami L. Kashyap (SSPR, 1996)

The Normalized String Editing Problem Revisited. - B. John Oommen; K. Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 1996)

Graph Partitioning Using Learning Automata. - B. John Oommen; Edward V. de St. Croix (IEEE Trans. Computers, 1996)

Numerical Similarity and Dissimilarity Measures Between Two Trees. - B. John Oommen; K. Zhang; William Lee (IEEE Trans. Computers, 1996)

Arbitrary distance function estimation using discrete vector quantization. - B. John Oommen; I. Kuban Altmel; Necati Aras (ICNN, 1997)

Generalized Swap-with-Parent Schemes for Self-Organizing Sequential Linear Lists. - B. John Oommen; Juan Dong (ISAAC, 1997)

On the Optimal Search Problem: The Case when the Target Distribution is Unknown. - Qingxin Zhu; B. John Oommen (SCCC, 1997)

Vector Quantization for Arbitrary Distance Function Estimation. - I. Kuban Altinel; B. John Oommen; Necati Aras (INFORMS J. Comput., 1997)

Moment-Preserving Piecewise Linear Approximations of Signals and Images. - Thai B. Nguyen; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 1997)

Pattern recognition of strings with substitutions, insertions, deletions and generalized transpositions. - B. John Oommen; Richard K. S. Loke (Pattern Recognit., 1997)

Stochastic searching on the line and its applications to parameter learning in nonlinear optimization. - B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 1997)

String taxonomy using learning automata. - B. John Oommen; Edward V. de St. Croix (IEEE Trans. Syst. Man Cybern. Part B, 1997)

A Fast Efficient Solution to the Capacity Assignment Problem Using Discretized Learning Automata. - B. John Oommen; T. Dale Roberts (IEA/AIE (Vol. 2), 1998)

The Noisy Subsequence Tree Recognition Problem. - B. John Oommen; R. K. S. Loke (SSPR/SPR, 1998)

A formal theory for optimal and information theoretic syntactic pattern recognition. - B. John Oommen; Rangasami L. Kashyap (Pattern Recognit., 1998)

Discrete vector quantization for arbitrary distance function estimation. - B. John Oommen; I. Kuban Altinel; Necati Aras (IEEE Trans. Syst. Man Cybern. Part B, 1998)

Automata learning and intelligent tertiary searching for stochastic point location. - B. John Oommen; Govindachari Raghunath (IEEE Trans. Syst. Man Cybern. Part B, 1998)

Prototype Validation of the Rectangular Attribute Cardinality Map for Query Optimization in Database Systems. - Murali Thiyagarajah; B. John Oommen (BIS, 1999)

On Benchmarking Attribute Cardinality Maps for Database Systems Using the TPC-D Specification. - Murali Thiyagarajah; B. John Oommen (DEXA, 1999)

Prototype Validation of the Trapezoidal Attribute Cardinality Map for Query Optimization in Database Systems. - Murali Thiyagarajah; B. John Oommen (ICEIS, 1999)

Query Result Size Estimation Using a Novel Histogram-like Technique: The Rectangular Attribute Cardinality Map. - B. John Oommen; Murali Thiyagarajah (IDEAS, 1999)

On Solving the Capacity Assignment Problem Using Continous Learning Automata. - B. John Oommen; T. Dale Roberts (IEA/AIE, 1999)

The Kohonen network incorporating explicit statistics and its application to the travelling salesman problem. - Necati Aras; B. John Oommen; I. Kuban Altinel (Neural Networks, 1999)

Designing syntactic pattern classifiers using vector quantization and parametric string editing. - B. John Oommen; R. K. S. Loke (IEEE Trans. Syst. Man Cybern. Part B, 1999)

A Kohonen-like Decomposition Method for the Traveling Salesman Problem: KNIESDECOMPOSE. - Necati Aras; I. Kuban Altinel; B. John Oommen (ECAI, 2000)

An Empirical Comparison of Histogram-Like Techniques for Query Optimization. - B. John Oommen; Luis Rueda 001 (ICEIS, 2000)

Query Result Size Estimation Using the Trapezoidal Attribute Cardinality Map. - B. John Oommen; Murali Thiyagarajah (IDEAS, 2000)

A Formalism for Building Causal Polytree Structures Using Data Distributions. - M. Ouerd; B. John Oommen; Stan Matwin (ISMIS, 2000)

The Foundational Theory of Optimal Bayesian Pairwise Linear Classifiers. - Luis Rueda 001; B. John Oommen (SSPR/SPR, 2000)

Fast, efficient and accurate solutions to the Hamiltonian path problem using neural approaches. - I. Kuban Altinel; Necati Aras; B. John Oommen (Comput. Oper. Res., 2000)

Continuous Learning Automata Solutions to the Capacity Assignment Problem. - B. John Oommen; T. Dale Roberts (IEEE Trans. Computers, 2000)

Resolving Minsky's Paradox: The d-Dimensional Normal Distribution Case. - Luís G. Rueda; B. John Oommen (Australian Joint Conference on Artificial Intelligence, 2001)

Histogram Methods in Query Optimization: The Relation between Accuracy and Optimality. - B. John Oommen; Luís G. Rueda (DASFAA, 2001)

A New Geometric Tool for Pattern Recognition - An Algorithm for Real Time Insertion of Layered Segment Trees. - Gopal Racherla; Sridhar Radhakrishnan; B. John Oommen (ICAPR, 2001)

Distance Bias Adjustment Bootstrap Estimation for Bhattacharyya Error Bound in Classifiers. - B. John Oommen; Qun Wang (PRIS, 2001)

Enhanced static Fano coding. - Luís G. Rueda; B. John Oommen (SMC, 2001)

On the Pattern Recognition of Noisy Subsequence Trees. - B. John Oommen; R. K. S. Loke (IEEE Trans. Pattern Anal. Mach. Intell., 2001)

Continuous and discretized pursuit learning schemes: various algorithms and their comparison. - B. John Oommen; M. Agache (IEEE Trans. Syst. Man Cybern. Part B, 2001)

Optimizing Kernel-Based Nonlinear Subspace Methods Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (Australian Joint Conference on Artificial Intelligence, 2002)

On Utilizing LVQ3-Type Algorithms to Enhance Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (PRIS, 2002)

Using Pattern Recognition Techniques to Derive a Formal Analysis of Why Heuristics Functions Work. - B. John Oommen; Luís G. Rueda (PRIS, 2002)

Creative prototype reduction schemes: a taxonomy and ranking. - Sang-Woon Kim; B. John Oommen (SMC (2), 2002)

Data generation for testing DAG-structured Bayesian networks. - Ouerd Messaouda; B. John Oommen; Stan Matwin (SMC, 2002)

Recursive Prototype Reduction Schemes Applicable for Large Data Sets. - Sang-Woon Kim; B. John Oommen (SSPR/SPR, 2002)

The Efficiency of Histogram-like Techniques for Database Query Optimization. - B. John Oommen; Luís G. Rueda (Comput. J., 2002)

On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case. - Luís G. Rueda; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 2002)

Enhanced layered segment trees: a pragmatic data structure for real-time processing of geometric objects. - Gopal Racherla; Sridhar Radhakrishnan; B. John Oommen (Pattern Recognit., 2002)

Generalized pursuit learning schemes: new families of continuous and discretized learning automata. - M. Agache; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2002)

Discretized learning automata solutions to the capacity assignment problem for prioritized networks. - B. John Oommen; T. Dale Roberts (IEEE Trans. Syst. Man Cybern. Part B, 2002)

Enhancing Caching in Distributed Databases Using Intelligent Polytree Representations. - Ouerd Messaouda; B. John Oommen; Stan Matwin (AI, 2003)

On How to Learn from a Stochastic Teacher or a Stochastic Compulsive Liar of Unknown Identity. - B. John Oommen; Govindachari Raghunath; Benjamin Kuipers (Australian Conference on Artificial Intelligence, 2003)

A new histogram method for sparse attributes: the averaged rectangular attribute cardinality map. - B. John Oommen; Jing Chen (ISICT, 2003)

A self-organizing method for map reconstruction. - I. Kuban Altinel; Necati Aras; B. John Oommen (NNSP, 2003)

Classification Error-Rate Estimation Using New Pseudo-Sample Bootstrap Methods. - Qun Wang; B. John Oommen (PRIS, 2003)

A brief taxonomy and ranking of creative prototype reduction schemes. - Sang-Woon Kim; B. John Oommen (Pattern Anal. Appl., 2003)

Enhancing prototype reduction schemes with LVQ3-type algorithms. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2003)

On optimal pairwise linear classifiers for normal distributions: the d-dimensional case. - Luís G. Rueda; B. John Oommen (Pattern Recognit., 2003)

A Kohonen-like decomposition method for the Euclidean traveling salesman problem-KNIES_DECOMPOSE. - Necati Aras; I. Kuban Altinel; B. John Oommen (IEEE Trans. Neural Networks, 2003)

Benchmarking attribute cardinality maps for database systems using the TPC-D specifications. - B. John Oommen; Murali Thiyagarajah (IEEE Trans. Syst. Man Cybern. Part B, 2003)

Deterministic Majority filters applied to stochastic sorting. - B. John Oommen; Jack R. Zgierski; Doron Nussbaum (ACM Southeast Regional Conference, 2004)

Adaptive Algorithms for Routing and Traffic Engineering in Stochastic Networks. - Sudip Misra; B. John Oommen (AAAI, 2004)

On Families of New Adaptive Compression Algorithms Suitable for Time-Varying Source Data. - Luís G. Rueda; B. John Oommen (ADVIS, 2004)

Selecting Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers Using Intelligent Search Methods. - Sang-Woon Kim; B. John Oommen (Australian Conference on Artificial Intelligence, 2004)

Stochastic Learning Automata-Based Dynamic Algorithms for the Single Source Shortest Path Problem. - Sudip Misra; B. John Oommen (IEA/AIE, 2004)

Generalized pursuit learning algorithms for shortest path routing tree computation. - Sudip Misra; B. John Oommen (ISCC, 2004)

Stochastic Sorting Using Deterministic Consecutive and Leader Filters. - B. John Oommen; Jack R. Zgierski; Doron Nussbaum (MSV/AMCS, 2004)

Recent Results on Learning from Stochastic Teachers and Compulsive Liars/Con-Men. - B. John Oommen (PRIS, 2004)

On Designing Pattern Classifiers Using Artificially Created Bootstrap Samples. - Qun Wang; B. John Oommen (PRIS, 2004)

Dictionary-Based Syntactic Pattern Recognition Using Tries. - B. John Oommen; Ghada Badr (SSPR/SPR, 2004)

A New Family of Weak Estimators for Training in Non-stationary Distributions. - B. John Oommen; Luís G. Rueda (SSPR/SPR, 2004)

GPSPA: a new adaptive algorithm for maintaining shortest path routing trees in stochastic networks. - Sudip Misra; B. John Oommen (Int. J. Commun. Syst., 2004)

A nearly-optimal Fano-based coding algorithm. - Luís G. Rueda; B. John Oommen (Inf. Process. Manag., 2004)

A formal approach to using data distributions for building causal polytree structures. - M. Ouerd; B. John Oommen; Stan Matwin (Inf. Sci., 2004)

On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2004)

Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2004)

On using conditional rotations and randomized heuristics for self-organizing ternary search tries. - Ghada Badr; B. John Oommen (ACM Southeast Regional Conference (1), 2005)

Time-Varying Prototype Reduction Schemes Applicable for Non-stationary Data Sets. - Sang-Woon Kim; B. John Oommen (Australian Conference on Artificial Intelligence, 2005)

A Look-Ahead Branch and Bound Pruning Scheme for Trie-Based Approximate String Matching. - Ghada Badr; B. John Oommen (CORES, 2005)

Neural Network-Based Chaotic Pattern Recognition - Part 2: Stability and Algorithmic Issues. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (CORES, 2005)

Enhancing Trie-Based Syntactic Pattern Recognition Using AI Heuristic Search Strategies. - Ghada Badr; B. John Oommen (ICAPR (1), 2005)

A Fixed-Structure Learning Automaton Solution to the Stochastic Static Mapping Problem. - Geir Horn; B. John Oommen (IPDPS, 2005)

New Algorithms for Maintaining All-Pairs Shortest Paths. - Sudip Misra; B. John Oommen (ISCC, 2005)

Efficient Adaptive Data Compression Using Fano Binary Search Trees. - Luís G. Rueda; B. John Oommen (ISCIS, 2005)

On Utilizing Stochastic Learning Weak Estimators for Training and Classification of Patterns with Non-stationary Distributions. - B. John Oommen; Luís G. Rueda (KI, 2005)

Modeling Inaccurate Perception: Desynchronization Issues of a Chaotic Pattern Recognition Neural Network. - Dragos Calitoiu; B. John Oommen; Dorin Nusbaumm (SCIA, 2005)

A formal analysis of why heuristic functions work. - B. John Oommen; Luís G. Rueda (Artif. Intell., 2005)

Self-Adjusting of Ternary Search Tries Using Conditional Rotations and Randomized Heuristics. - Ghada Hany Badr; B. John Oommen (Comput. J., 2005)

On Utilizing Search Methods to Select Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Pattern Anal. Mach. Intell., 2005)

Dynamic algorithms for the shortest path routing problem: learning automata-based solutions. - Sudip Misra; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2005)

The averaged mappings problem: statement, applications, and approximate solution. - Xavier Hilaire; B. John Oommen (ACM Southeast Regional Conference, 2006)

On Optimizing the k-Ward Micro-aggregation Technique for Secure Statistical Databases. - Ebaa Fayyoumi; B. John Oommen (ACISP, 2006)

Turning Lights Out with DQ-Learning. - Denis V. Batalov; B. John Oommen (Artificial Intelligence and Applications, 2006)

Empirical Verification of a Strategy for Unbounded Resolution in Finite Player Goore Games. - B. John Oommen; Ole-Christoffer Granmo; Asle Pedersen (Australian Conference on Artificial Intelligence, 2006)

On Utilizing Attribute Cardinality Maps to Enhance Query Optimization in the Oracle Database System. - B. John Oommen; Jing Chen (ICEIS (1), 2006)

On Enhancing Query Optimization in the Oracle Database System by Utilizing Attribute Cardinality Maps. - B. John Oommen; Jing Chen (ICEIS (Selected Papers), 2006)

On Optimizing Dissimilarity-Based Classification Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (ICIAR (1), 2006)

On Allocating Limited Sampling Resources Using a Learning Automata-based Solution to the Fractional Knapsack Problem. - Ole-Christoffer Granmo; B. John Oommen (Intelligent Information Systems, 2006)

A Stochastic Random-Races Algorithm for Routing in MPLS Traffic Engineering. - B. John Oommen; Sudip Misra; Ole-Christoffer Granmo (INFOCOM, 2006)

A Fixed Structure Learning Automaton Micro-aggregation Technique for Secure Statistical Databases. - Ebaa Fayyoumi; B. John Oommen (Privacy in Statistical Databases, 2006)

An Application of a Game of Discrete Generalised Pursuit Automata to Solve a Multi-Constraint Partitioning Problem. - Geir Horn; B. John Oommen (SMC, 2006)

On Optimizing Kernel-Based Fisher Discriminant Analysis Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (SSPR/SPR, 2006)

On the Theory and Applications of Sequence Based Estimation of Independent Binomial Random Variables. - B. John Oommen; Sang-Woon Kim; Geir Horn (SSPR/SPR, 2006)

Lists on Lists: A Framework for Self-organizing Lists in Environments with Locality of Reference. - Abdelrahman Amer; B. John Oommen (WEA, 2006)

A Fault-Tolerant Routing Algorithm for Mobile Ad Hoc Networks Using a Stochastic Learning-Based Weak Estimation Procedure. - B. John Oommen; Sudip Misra (WiMob, 2006)

A fast and efficient nearly-optimal adaptive Fano coding scheme. - Luis Rueda 001; B. John Oommen (Inf. Sci., 2006)

A novel look-ahead optimization strategy for trie-based approximate string matching. - Ghada Badr; B. John Oommen (Pattern Anal. Appl., 2006)

Prototype reduction schemes applicable for non-stationary data sets. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2006)

Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments. - B. John Oommen; Luis Rueda 001 (Pattern Recognit., 2006)

An Efficient Dynamic Algorithm for Maintaining All-Pairs Shortest Paths in Stochastic Networks. - Sudip Misra; B. John Oommen (IEEE Trans. Computers, 2006)

On optimizing syntactic pattern recognition using tries and AI-based heuristic-search strategies. - Ghada Badr; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2006)

Parameter learning from stochastic teachers and stochastic compulsive liars. - B. John Oommen; Govindachari Raghunath; Benjamin Kuipers (IEEE Trans. Syst. Man Cybern. Part B, 2006)

Stochastic Automata-Based Estimators for Adaptively Compressing Files With Nonstationary Distributions. - Luis Rueda 001; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2006)

Analytic Results on the Hodgkin-Huxley Neural Network: Spikes Annihilation. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (Canadian AI, 2007)

The Pursuit Automaton Approach for Estimating All-Pairs Shortest Paths in Dynamically Changing Networks. - Sudip Misra; B. John Oommen (AINA Workshops (1), 2007)

Some Analysis on the Network of Bursting Neurons: Quantifying Behavioral Synchronization. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (Australian Conference on Artificial Intelligence, 2007)

On Using a Hierarchy of Twofold Resource Allocation Automata to Solve Stochastic Nonlinear Resource Allocation Problems. - Ole-Christoffer Granmo; B. John Oommen (Australian Conference on Artificial Intelligence, 2007)

Numerical Results on the Hodgkin-Huxley Neural Network: Spikes Annihilation. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (BVAI, 2007)

Using Stochastic AI Techniques to Achieve Unbounded Resolution in Finite Player Goore Games and its Applications. - B. John Oommen; Ole-Christoffer Granmo; Asle Pedersen (CIG, 2007)

A Novel Method for Micro-Aggregation in Secure Statistical Databases Using Association and Interaction. - B. John Oommen; Ebaa Fayyoumi (ICICS, 2007)

On Using Learning Automata to Model a Student's Behavior in a Tutorial-like System. - M. Khaled Hashem; B. John Oommen (IEA/AIE, 2007)

Stochastic Point Location in Non-stationary Environments and Its Applications. - B. John Oommen; Sang-Woon Kim; Mathew Samuel; Ole-Christoffer Granmo (IEA/AIE, 2007)

Using learning automata to model the behavior of a teacher in a tutorial-like system. - M. Khaled Hashem; B. John Oommen (SMC, 2007)

Using learning automata to model a student-classroom interaction in a tutorial-like system. - M. Khaled Hashem; B. John Oommen (SMC, 2007)

A Novel Framework for Self-Organizing Lists in Environments with Locality of Reference: Lists-on-Lists. - Abdelrahman Amer; B. John Oommen (Comput. J., 2007)

Periodicity and stability issues of a chaotic pattern recognition neural network. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (Pattern Anal. Appl., 2007)

Breadth-first search strategies for trie-based syntactic pattern recognition. - B. John Oommen; Ghada Hany Badr (Pattern Anal. Appl., 2007)

On using prototype reduction schemes to optimize dissimilarity-based classification. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2007)

On the estimation of independent binomial random variables using occurrence and sequential information. - B. John Oommen; Sang-Woon Kim; Geir Horn (Pattern Recognit., 2007)

Routing Bandwidth-Guaranteed Paths in MPLS Traffic Engineering: A Multiple Race Track Learning Approach. - B. John Oommen; Sudip Misra; Ole-Christoffer Granmo (IEEE Trans. Computers, 2007)

Goal-oriented optimal subset selection of correlated multimedia streams. - Pradeep K. Atrey; Mohan S. Kankanhalli; B. John Oommen (ACM Trans. Multim. Comput. Commun. Appl., 2007)

Desynchronizing a Chaotic Pattern Recognition Neural Network to Model Inaccurate Perception. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (IEEE Trans. Syst. Man Cybern. Part B, 2007)

Learning Automata-Based Solutions to the Nonlinear Fractional Knapsack Problem With Applications to Optimal Resource Allocation. - Ole-Christoffer Granmo; B. John Oommen; Svein Arild Myrer; Morten Goodwin Olsen (IEEE Trans. Syst. Man Cybern. Part B, 2007)

Enhancing Micro-Aggregation Technique by Utilizing Dependence-Based Information in Secure Statistical Databases. - B. John Oommen; Ebaa Fayyoumi (ACISP, 2008)

A Fast Computation of Inter-class Overlap Measures Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (Canadian AI, 2008)

An AI-Based Causal Strategy for Securing Statistical Databases Using Micro-aggregation. - B. John Oommen; Ebaa Fayyoumi (Australasian Conference on Artificial Intelligence, 2008)

Chernoff-Based Multi-class Pairwise Linear Dimensionality Reduction. - Luis Rueda 001; Claudio Henríquez; B. John Oommen (CIARP, 2008)

A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Web Polling. - Ole-Christoffer Granmo; B. John Oommen (IEA/AIE, 2008)

Large scale modeling of the piriform cortex for analyzing antiepileptic effects. - Dragos Calitoiu; Doron Nussbaum; B. John Oommen (SpringSim, 2008)

Modeling and simulating a disease outbreak by learning a contagion parameter-based model. - B. John Oommen; Dragos Calitoiu (SpringSim, 2008)

Chaotic Pattern Recognition: The Spectrum of Properties of the Adachi Neural Network. - Ke Qin; B. John Oommen (SSPR/SPR, 2008)

Spikes annihilation in the Hodgkin-Huxley neuron. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (Biol. Cybern., 2008)

An efficient compression scheme for data communication which uses a new family of self-organizing binary search trees. - Luis Rueda 001; B. John Oommen (Int. J. Commun. Syst., 2008)

On Using Prototype Reduction Schemes to Optimize Kernel-Based Fisher Discriminant Analysis. - Sang-Woon Kim; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2008)

A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments. - B. John Oommen; Sang-Woon Kim; M. T. Samuel; Ole-Christoffer Granmo (IEEE Trans. Syst. Man Cybern. Part B, 2008)

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 (AICCSA, 2009)

On Using Adaptive Binary Search Trees to Enhance Self Organizing Maps. - César A. Astudillo; B. John Oommen (Australasian Conference on Artificial Intelligence, 2009)

Anomaly Detection in Dynamic Social Systems Using Weak Estimators. - Justin Zhan; B. John Oommen; Johanna Crisostomo (CSE (4), 2009)

A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling. - Ole-Christoffer Granmo; B. John Oommen (IEA/AIE, 2009)

Learning Automata Based Intelligent Tutorial-like System. - B. John Oommen; M. Khaled Hashem (KES (1), 2009)

On Utilizing Optimal and Information Theoretic Syntactic Modeling for Peptide Classification. - Eser Aygün; B. John Oommen; Zehra Cataltepe (PRIB, 2009)

An efficient pursuit automata approach for estimating stable all-pairs shortest paths in stochastic network environments. - Sudip Misra; B. John Oommen (Int. J. Commun. Syst., 2009)

Estimation of distributions involving unobservable events: the case of optimal search with unknown Target Distributions. - Qingxin Zhu; B. John Oommen (Pattern Anal. Appl., 2009)

On using prototype reduction schemes to enhance the computation of volume-based inter-class overlap measures. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2009)

Adachi-Like Chaotic Neural Networks Requiring Linear-Time Computations by Enforcing a Tree-Shaped Topology. - Ke Qin; B. John Oommen (IEEE Trans. Neural Networks, 2009)

Achieving Microaggregation for Secure Statistical Databases Using Fixed-Structure Partitioning-Based Learning Automata. - Ebaa Fayyoumi; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2009)

Cybernetics and Learning Automata. - B. John Oommen; Sudip Misra (Handbook of Automation, 2009)

A Novel Self Organizing Map Which Utilizes Imposed Tree-Based Topologies. - César A. Astudillo; B. John Oommen (Computer Recognition Systems 3, 2009)

Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems. - Ole-Christoffer Granmo; B. John Oommen (Intelligent Systems for Knowledge Management, 2009)

Potential AI Strategies to Solve the Commons Game: A Position Paper. - Petro Verkhogliad; B. John Oommen (Canadian AI, 2010)

On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes. - Sang-Woon Kim; B. John Oommen (Australasian Conference on Artificial Intelligence, 2010)

On using Simulation and Stochastic Learning for Pattern Recognition When Training Data is Unavailable - The Case of Disease Outbreak. - Dragos Calitoiu; B. John Oommen (ICAART (1), 2010)

A Generic Solution to Multi-Armed Bernoulli Bandit Problems based on Random Sampling from Sibling Conjugate Priors. - Thomas Norheim; Terje Brådland; Ole-Christoffer Granmo; B. John Oommen (ICAART (1), 2010)

A Learning Automata Based Solution to Service Selection in Stochastic Environments. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen (IEA/AIE (3), 2010)

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 (PRICAI, 2010)

On simulating episodic events against a background of noise-like non-episodic events. - Colin Bellinger; B. John Oommen (SummerSim, 2010)

Language Detection and Tracking in Multilingual Documents Using Weak Estimators. - Aleksander Stensby; B. John Oommen; Ole-Christoffer Granmo (SSPR/SPR, 2010)

Modeling a Domain in a Tutorial-like System Using Learning Automata. - B. John Oommen; M. Khaled Hashem (Acta Cybern., 2010)

Optimal sampling for estimation with constrained resources using a learning automaton-based solution for the nonlinear fractional knapsack problem. - Ole-Christoffer Granmo; B. John Oommen (Appl. Intell., 2010)

Peptide classification using optimal and information theoretic syntactic modeling. - Eser Aygün; B. John Oommen; Zehra Cataltepe (Pattern Recognit., 2010)

Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes. - Luis Rueda 001; B. John Oommen; Claudio Henríquez (Pattern Recognit., 2010)

A survey on statistical disclosure control and micro-aggregation techniques for secure statistical databases. - Ebaa Fayyoumi; B. John Oommen (Softw. Pract. Exp., 2010)

Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata. - Ole-Christoffer Granmo; B. John Oommen (IEEE Trans. Computers, 2010)

Fault-tolerant routing in adversarial mobile ad hoc networks: an efficient route estimation scheme for non-stationary environments. - B. John Oommen; Sudip Misra (Telecommun. Syst., 2010)

Solving Multiconstraint Assignment Problems Using Learning Automata. - Geir Horn; B. John Oommen (IEEE Trans. Syst. Man Cybern. Part B, 2010)

Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution. - Sudip Misra; B. John Oommen; Sreekeerthy Yanamandra; Mohammad S. Obaidat (IEEE Trans. Syst. Man Cybern. Part B, 2010)

On Utilizing Association and Interaction Concepts for Enhancing Microaggregation in Secure Statistical Databases. - B. John Oommen; Ebaa Fayyoumi (IEEE Trans. Syst. Man Cybern. Part B, 2010)

Modeling a Student-Classroom Interaction in a Tutorial-Like System Using Learning Automata. - B. John Oommen; M. Khaled Hashem (IEEE Trans. Syst. Man Cybern. Part B, 2010)

Modeling a Student's Behavior in a Tutorial-Like System Using Learning Automata. - B. John Oommen; M. Khaled Hashem (IEEE Trans. Syst. Man Cybern. Part B, 2010)

A New Frontier in Novelty Detection: Pattern Recognition of Stochastically Episodic Events. - Colin Bellinger; B. John Oommen (ACIIDS (1), 2011)

Semi-Supervised Classification Using Tree-Based Self-Organizing Maps. - César A. Astudillo; B. John Oommen (Australasian Conference on Artificial Intelligence, 2011)

Tracking the Preferences of Users Using Weak Estimators. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen (Australasian Conference on Artificial Intelligence, 2011)

On the analysis of a new Markov chain which has applications in AI and machine learning. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen (CCECE, 2011)

Using Artificial Intelligence Techniques for Strategy Generation in the Commons Game. - Petro Verkhogliad; B. John Oommen (HAIS (1), 2011)

A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen (HAIS (1), 2011)

The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata. - Xuan Zhang 007; Ole-Christoffer Granmo; B. John Oommen (IEA/AIE (2), 2011)

Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems. - Xuan Zhang 007; B. John Oommen; Ole-Christoffer Granmo (AIAI, 2011)

Anomaly detection using weak estimators. - Justin Zhan; B. John Oommen; Johanna Crisostomo (ISI, 2011)

On Merging the Fields of Neural Networks and Adaptive Data Structures to Yield New Pattern Recognition Methodologies. - B. John Oommen (PReMI, 2011)

Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem. - Ole-Christoffer Granmo; B. John Oommen (Eng. Appl. Artif. Intell., 2011)

Imposing tree-based topologies onto self organizing maps. - César A. Astudillo; B. John Oommen (Inf. Sci., 2011)

Anomaly Detection in Dynamic Systems Using Weak Estimators. - Justin Zhan; B. John Oommen; Johanna Crisostomo (ACM Trans. Internet Techn., 2011)

A User-Centric Approach for Personalized Service Provisioning in Pervasive Environments. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen; Martin Gerdes; Frank Reichert (Wirel. Pers. Commun., 2011)

Optimal "Anti-Bayesian" Parametric Pattern Classification Using Order Statistics Criteria. - Anu Thomas; B. John Oommen (CIARP, 2012)

A Fast Heuristic Solution for the Commons Game. - Rokhsareh Sakhravi; Masoud T. Omran; B. John Oommen (DCAI, 2012)

A novel Stochastic Discretized Weak Estimator operating in non-stationary environments. - Anis Yazidi; B. John Oommen; Ole-Christoffer Granmo (ICNC, 2012)

Optimal "Anti-Bayesian" Parametric Pattern Classification for the Exponential Family Using Order Statistics Criteria. - Anu Thomas; B. John Oommen (ICIAR (1), 2012)

A Stochastic Search on the Line-Based Solution to Discretized Estimation. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen (IEA/AIE, 2012)

A Hierarchical Learning Scheme for Solving the Stochastic Point Location Problem. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen; Morten Goodwin Olsen (IEA/AIE, 2012)

Discretized Bayesian Pursuit - A New Scheme for Reinforcement Learning. - Xuan Zhang 007; Ole-Christoffer Granmo; B. John Oommen (IEA/AIE, 2012)

Service selection in stochastic environments: a learning-automaton based solution. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen (Appl. Intell., 2012)

The entire range of Chaotic pattern recognition properties possessed by the Adachi neural network. - Ke Qin; B. John Oommen (Intell. Decis. Technol., 2012)

An Adaptive Approach to Learning the Preferences of Users in a Social Network Using Weak Estimators. - B. John Oommen; Anis Yazidi; Ole-Christoffer Granmo (J. Inf. Process. Syst., 2012)

On using prototype reduction schemes to optimize locally linear reconstruction methods. - Sang-Woon Kim; B. John Oommen (Pattern Recognit., 2012)

Large-scale neuro-modeling for understanding and explaining some brain-related chaotic behavior. - Dragos Calitoiu; B. John Oommen; Doron Nussbaum (Simul., 2012)

On the Pattern Recognition and Classification of Stochastically Episodic Events. - Colin Bellinger; B. John Oommen (Trans. Comput. Collect. Intell., 2012)

Modeling a Teacher in a Tutorial-like System Using Learning Automata. - B. John Oommen; M. Khaled Hashem (Trans. Comput. Collect. Intell., 2012)

A New Paradigm for Pattern Classification: Nearest Border Techniques. - Yifeng Li 001; B. John Oommen; Alioune Ngom; Luis Rueda 001 (Australasian Conference on Artificial Intelligence, 2013)

Ultimate Order Statistics-Based Prototype Reduction Schemes. - Anu Thomas; B. John Oommen (Australasian Conference on Artificial Intelligence, 2013)

A Novel Border Identification Algorithm Based on an "Anti-Bayesian" Paradigm. - Anu Thomas; B. John Oommen (CAIP (1), 2013)

On Achieving Near-Optimal "Anti-Bayesian" Order Statistics-Based Classification for Asymmetric Exponential Distributions. - Anu Thomas; B. John Oommen (CAIP (1), 2013)

Classification of Multi-dimensional Distributions Using Order Statistics Criteria. - Anu Thomas; B. John Oommen (CORES, 2013)

On Using the Theory of Regular Functions to Prove the ε-Optimality of the Continuous Pursuit Learning Automaton. - Xuan Zhang 007; Ole-Christoffer Granmo; B. John Oommen; Lei Jiao 001 (IEA/AIE, 2013)

Channel selection in Cognitive Radio Networks: A Switchable Bayesian Learning Automata approach. - Xuan Zhang 007; Lei Jiao 001; Ole-Christoffer Granmo; B. John Oommen (PIMRC, 2013)

On Applying Adaptive Data Structures to Multi-Player Game Playing. - Spencer Polk; B. John Oommen (SGAI Conf., 2013)

On Enhancing Recent Multi-player Game Playing Strategies Using a Spectrum of Adaptive Data Structures. - Spencer Polk; B. John Oommen (TAAI, 2013)

On incorporating the paradigms of discretization and Bayesian estimation to create a new family of pursuit learning automata. - Xuan Zhang 007; Ole-Christoffer Granmo; B. John Oommen (Appl. Intell., 2013)

The Use of Weak estimators to Achieve Language Detection and Tracking in Multilingual Documents. - Aleksander Stensby; B. John Oommen; Ole-Christoffer Granmo (Int. J. Pattern Recognit. Artif. Intell., 2013)

On utilizing dependence-based information to enhance micro-aggregation for secure statistical databases. - B. John Oommen; Ebaa Fayyoumi (Pattern Anal. Appl., 2013)

On achieving semi-supervised pattern recognition by utilizing tree-based SOMs. - César A. Astudillo; B. John Oommen (Pattern Recognit., 2013)

The fundamental theory of optimal "Anti-Bayesian" parametric pattern classification using order statistics criteria. - Anu Thomas; B. John Oommen (Pattern Recognit., 2013)

Order statistics-based parametric classification for multi-dimensional distributions. - Anu Thomas; B. John Oommen (Pattern Recognit., 2013)

Ideal Chaotic Pattern Recognition Is Achievable: The Ideal-M-AdNN - Its Design and Properties. - Ke Qin; B. John Oommen (Trans. Comput. Collect. Intell., 2013)

Modeling the "Learning Process" of the Teacher in a Tutorial-Like System Using Learning Automata. - B. John Oommen; M. Khaled Hashem (IEEE Trans. Cybern., 2013)

Learning-Automaton-Based Online Discovery and Tracking of Spatiotemporal Event Patterns. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen (IEEE Trans. Cybern., 2013)

On Utilizing Stochastic Non-linear Fractional Bin Packing to Resolve Distributed Web Crawling. - Anis Yazidi; B. John Oommen; Ole-Christoffer Granmo; Morten Goodwin (CSE, 2014)

A Bayesian Learning Automata-Based Distributed Channel Selection Scheme for Cognitive Radio Networks. - Lei Jiao 001; Xuan Zhang 007; Ole-Christoffer Granmo; B. John Oommen (IEA/AIE (2), 2014)

Using the Theory of Regular Functions to Formally Prove the ε-Optimality of Discretized Pursuit Learning Algorithms. - Xuan Zhang 007; B. John Oommen; Ole-Christoffer Granmo; Lei Jiao 001 (IEA/AIE (1), 2014)

Cryptanalysis of a Cryptographic Algorithm that Utilizes Chaotic Neural Networks. - Ke Qin; B. John Oommen (ISCIS, 2014)

Fast BMU Search in SOMs Using Random Hyperplane Trees. - César A. Astudillo; B. John Oommen (PRICAI, 2014)

A formal proof of the ε-optimality of absorbing continuous pursuit algorithms using the theory of regular functions. - Xuan Zhang 007; Ole-Christoffer Granmo; B. John Oommen; Lei Jiao 001 (Appl. Intell., 2014)

Logistic Neural Networks: Their chaotic and pattern recognition properties. - Qin Ke; B. John Oommen (Neurocomputing, 2014)

Topology-oriented self-organizing maps: a survey. - César A. Astudillo; B. John Oommen (Pattern Anal. Appl., 2014)

Self-organizing maps whose topologies can be learned with adaptive binary search trees using conditional rotations. - César A. Astudillo; B. John Oommen (Pattern Recognit., 2014)

"Anti-Bayesian" parametric pattern classification using order statistics criteria for some members of the exponential family. - B. John Oommen; Anu Thomas (Pattern Recognit., 2014)

Corrigendum to three papers that deal with "Anti"-Bayesian Pattern Recognition [Pattern Recognition]. - Anu Thomas; B. John Oommen (Pattern Recognit., 2014)

On the Existence and Heuristic Computation of the Solution for the Commons Game. - Rokhsareh Sakhravi; Masoud T. Omran; B. John Oommen (Trans. Comput. Collect. Intell., 2014)

A Novel Strategy for Solving the Stochastic Point Location Problem Using a Hierarchical Searching Scheme. - Anis Yazidi; Ole-Christoffer Granmo; B. John Oommen; Morten Goodwin Olsen (IEEE Trans. Cybern., 2014)

Particle Field Optimization: A New Paradigm for Swarm Intelligence. - Nathan Bell; B. John Oommen (AAMAS, 2015)

Space and depth-related enhancements of the history-ADS strategy in game playing. - Spencer Polk; B. John Oommen (CIG, 2015)

Solving Stochastic Root-Finding with adaptive d-ary search. - Anis Yazidi; B. John Oommen (EAIS, 2015)

Text Classification Using Novel "Anti-Bayesian" Techniques. - B. John Oommen; Richard Khoury; Aron Schmidt (ICCCI (1), 2015)

Enhancing History-Based Move Ordering in Game Playing Using Adaptive Data Structures. - Spencer Polk; B. John Oommen (ICCCI (1), 2015)

Pattern Recognition using the TTOCONROT. - César A. Astudillo; B. John Oommen (IEA/AIE, 2015)

A Novel Clustering Algorithm Based on a Non-parametric "Anti-Bayesian" Paradigm. - Hugo Lewi Hammer; Anis Yazidi; B. John Oommen (IEA/AIE, 2015)

Novel AI Strategies for Multi-Player Games at Intermediate Board States. - Spencer Polk; B. John Oommen (IEA/AIE, 2015)

On Distinguishing between Reliable and Unreliable Sensors Without a Knowledge of the Ground Truth. - Anis Yazidi; B. John Oommen; Morten Goodwin Olsen (WI-IAT (2), 2015)

Pattern classification using a new border identification paradigm: The nearest border technique. - Yifeng Li 001; B. John Oommen; Alioune Ngom; Luis Rueda 001 (Neurocomputing, 2015)

Concept Drift Detection Using Online Histogram-Based Bayesian Classifiers. - César A. Astudillo; Javier I. González; B. John Oommen; Anis Yazidi (Australasian Conference on Artificial Intelligence, 2016)

A Cluster Analysis of Stock Market Data Using Hierarchical SOMs. - César A. Astudillo; Jorge Poblete; Marina Resta; B. John Oommen (Australasian Conference on Artificial Intelligence, 2016)

On the Foundations of Multinomial Sequence Based Estimation. - B. John Oommen; Sang-Woon Kim (ICCCI (1), 2016)

Dynamic Ordering of Firewall Rules Using a Novel Swapping Window-based Paradigm. - Ratish Mohan; Anis Yazidi; Boning Feng; B. John Oommen (ICCNS, 2016)

Multinomial Sequence Based Estimation Using Contiguous Subsequences of Length Three. - B. John Oommen; Sang-Woon Kim (ICIAR, 2016)

Challenging Established Move Ordering Strategies with Adaptive Data Structures. - Spencer Polk; B. John Oommen (IEA/AIE, 2016)

On the Online Classification of Data Streams Using Weak Estimators. - Hanane Tavasoli; B. John Oommen; Anis Yazidi (IEA/AIE, 2016)

Optimizing channel selection for cognitive radio networks using a distributed Bayesian learning automata-based approach. - Lei Jiao 001; Xuan Zhang 007; B. John Oommen; Ole-Christoffer Granmo (Appl. Intell., 2016)

A formal proof of the 𝜀-optimality of discretized pursuit algorithms. - Xuan Zhang 007; B. John Oommen; Ole-Christoffer Granmo; Lei Jiao 001 (Appl. Intell., 2016)

Stochastic discretized learning-based weak estimation: a novel estimation method for non-stationary environments. - Anis Yazidi; B. John Oommen; Geir Horn; Ole-Christoffer Granmo (Pattern Recognit., 2016)

Text Classification Using "Anti"-Bayesian Quantile Statistics-Based Classifiers. - B. John Oommen; Richard Khoury; Aron Schmidt (Trans. Comput. Collect. Intell., 2016)

On Achieving History-Based Move Ordering in Adversarial Board Games Using Adaptive Data Structures. - Spencer Polk; B. John Oommen (Trans. Comput. Collect. Intell., 2016)

Novel Discretized Weak Estimators Based on the Principles of the Stochastic Search on the Line Problem. - Anis Yazidi; B. John Oommen (IEEE Trans. Cybern., 2016)

A Higher-Fidelity Frugal Quantile Estimator. - Anis Yazidi; Hugo Lewi Hammer; B. John Oommen (ADMA, 2017)

Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments. - Anis Yazidi; B. John Oommen; Morten Goodwin (ADMA, 2017)

On using novel "Anti-Bayesian" techniques for the classification of dynamical data streams. - Hugo Lewi Hammer; Anis Yazidi; B. John Oommen (CEC, 2017)

Enhancing English-Japanese Translation Using Syntactic Pattern Recognition Methods. - Thomas McMahon; B. John Oommen (CORES, 2017)

Novel Results on Random Walk-Jump Chains That Possess Tree-Based Transitions. - Anis Yazidi; B. John Oommen (CORES, 2017)

Partitioning in signal processing using the object migration automaton and the pursuit paradigm. - Abdolreza Shirvani; B. John Oommen (MLSP, 2017)

Scheduling Domestic Shiftable Loads in Smart Grids: A Learning Automata-Based Scheme. - Rajan Thapa; Lei Jiao 001; B. John Oommen; Anis Yazidi (SmartGIFT, 2017)

A novel abstraction for swarm intelligence: particle field optimization. - Nathan Bell; B. John Oommen (Auton. Agents Multi Agent Syst., 2017)

Occlusion-based estimation of independent multinomial random variables using occurrence and sequential information. - B. John Oommen; Sang-Woon Kim (Eng. Appl. Artif. Intell., 2017)

"Anti-Bayesian" flat and hierarchical clustering using symmetric quantiloids. - Hugo Lewi Hammer; Anis Yazidi; B. John Oommen (Inf. Sci., 2017)

A novel technique for stochastic root-finding: Enhancing the search with adaptive d-ary search. - Anis Yazidi; B. John Oommen (Inf. Sci., 2017)

The design of absorbing Bayesian pursuit algorithms and the formal analyses of their ε-optimality. - Xuan Zhang 007; B. John Oommen; Ole-Christoffer Granmo (Pattern Anal. Appl., 2017)

On Solving the Problem of Identifying Unreliable Sensors Without a Knowledge of the Ground Truth: The Case of Stochastic Environments. - Anis Yazidi; B. John Oommen; Morten Goodwin (IEEE Trans. Cybern., 2017)

On Using "Stochastic Learning on the Line" to Design Novel Distance Estimation Methods. - Jessica Havelock; B. John Oommen; Ole-Christoffer Granmo (IEA/AIE, 2018)

On Addressing the Challenges of Complex Stochastic Games Using "Representative" Moves. - Armando H. Taucer; Spencer Polk; B. John Oommen (AIAI, 2018)

The Hierarchical Continuous Pursuit Learning Automation for Large Numbers of Actions. - Anis Yazidi; Xuan Zhang 007; Lei Jiao 001; B. John Oommen (AIAI, 2018)

Novel Distance Estimation Methods Using "Stochastic Learning on the Line" Strategies. - Jessica Havelock; B. John Oommen; Ole-Christoffer Granmo (IEEE Access, 2018)

On Invoking Transitivity to Enhance the Pursuit-Oriented Object Migration Automata. - Abdolreza Shirvani; B. John Oommen (IEEE Access, 2018)

A Learning Automaton-Based Scheme for Scheduling Domestic Shiftable Loads in Smart Grids. - Rajan Thapa; Lei Jiao 001; B. John Oommen; Anis Yazidi (IEEE Access, 2018)

Higher-Fidelity Frugal and Accurate Quantile Estimation Using a Novel Incremental Discretized Paradigm. - Anis Yazidi; Hugo Hammer; B. John Oommen (IEEE Access, 2018)

Challenging state-of-the-art move ordering with Adaptive Data Structures. - Spencer Polk; B. John Oommen (Appl. Intell., 2018)

Novel threat-based AI strategies that incorporate adaptive data structures for multi-player board games. - Spencer Polk; B. John Oommen (Appl. Intell., 2018)

On optimizing firewall performance in dynamic networks by invoking a novel swapping window-based paradigm. - Ratish Mohan; Anis Yazidi; Boning Feng; B. John Oommen (Int. J. Commun. Syst., 2018)

On achieving intelligent traffic-aware consolidation of virtual machines in a data center using Learning Automata. - Akaki Jobava; Anis Yazidi; B. John Oommen; Kyrre M. Begnum (J. Comput. Sci., 2018)

On enhancing the object migration automaton using the Pursuit paradigm. - Abdolreza Shirvani; B. John Oommen (J. Comput. Sci., 2018)

On the classification of dynamical data streams using novel "Anti-Bayesian" techniques. - Hugo Lewi Hammer; Anis Yazidi; B. John Oommen (Pattern Recognit., 2018)

Multi-Minimax: A New AI Paradigm for Simultaneously-Played Multi-player Games. - Nicolas Perez; B. John Oommen (Australasian Conference on Artificial Intelligence, 2019)

The Power of the "Pursuit" Learning Paradigm in the Partitioning of Data. - Abdolreza Shirvani; B. John Oommen (EANN, 2019)

Optimizing Self-organizing Lists-on-Lists Using Pursuit-Oriented Enhanced Object Partitioning. - O. Ekaba Bisong; B. John Oommen (ICIC (3), 2019)

Learning Automata-Based Solutions to the Multi-Elevator Problem. - Omar Ghaleb; B. John Oommen (ICIC (3), 2019)

On Using "Stochastic Learning on the Line" to Design Novel Distance Estimation Methods for Three-Dimensional Environments. - Jessica Havelock; B. John Oommen; Ole-Christoffer Granmo (IEA/AIE, 2019)

Optimizing Self-organizing Lists-on-Lists Using Enhanced Object Partitioning. - O. Ekaba Bisong; B. John Oommen (AIAI, 2019)

Learning Automata-Based Solutions to the Single Elevator Problem. - Omar Ghaleb; B. John Oommen (AIAI, 2019)

On utilizing weak estimators to achieve the online classification of data streams. - Hanane Tavasoli; B. John Oommen; Anis Yazidi (Eng. Appl. Artif. Intell., 2019)

Novel Block Diagonalization for Reducing Features and Computations in Medical Diagnosis. - Tahira Ghani; B. John Oommen (Australasian Conference on Artificial Intelligence, 2020)

Enhancing the Prediction of Lung Cancer Survival Rates Using 2D Features from 3D Scans. - Tahira Ghani; B. John Oommen (ICIAR (2), 2020)

User Grouping and Power Allocation in NOMA Systems: A Reinforcement Learning-Based Solution. - Rebekka Olsson Omslandseter; Lei Jiao 001; Yuanwei Liu; B. John Oommen (IEA/AIE, 2020)

Optimizing Self-organizing Lists-on-Lists Using Transitivity and Pursuit-Enhanced Object Partitioning. - O. Ekaba Bisong; B. John Oommen (AIAI (1), 2020)

A Novel Learning Automata-Based Strategy to Generate Melodies from Chordal Inputs. - Ibrahim Helmy; B. John Oommen (AIAI (1), 2020)

On enhancing the deadlock-preventing object migration automaton using the pursuit paradigm. - Abdolreza Shirvani; B. John Oommen (Pattern Anal. Appl., 2020)

The Hierarchical Continuous Pursuit Learning Automation: A Novel Scheme for Environments With Large Numbers of Actions. - Anis Yazidi; Xuan Zhang 007; Lei Jiao 001; B. John Oommen (IEEE Trans. Neural Networks Learn. Syst., 2020)

A Conclusive Analysis of the Finite-Time Behavior of the Discretized Pursuit Learning Automaton. - Xuan Zhang 007; Lei Jiao 001; B. John Oommen; Ole-Christoffer Granmo (IEEE Trans. Neural Networks Learn. Syst., 2020)

A Learning-Automata Based Solution for Non-equal Partitioning: Partitions with Common GCD Sizes. - Rebekka Olsson Omslandseter; Lei Jiao 001; B. John Oommen (IEA/AIE (2), 2021)

Object Migration Automata for Non-equal Partitioning Problems with Known Partition Sizes. - Rebekka Olsson Omslandseter; Lei Jiao 001; B. John Oommen (AIAI, 2021)

On utilizing an enhanced object partitioning scheme to optimize self-organizing lists-on-lists. - O. Ekaba Bisong; B. John Oommen (Evol. Syst., 2021)

On utilizing the transitivity pursuit-enhanced object partitioning to optimize self-organizing lists-on-lists. - O. Ekaba Bisong; B. John Oommen (Evol. Syst., 2021)

On solving single elevator-like problems using a learning automata-based paradigm. - Omar Ghaleb; B. John Oommen (Evol. Syst., 2021)

Nonparametric "anti-Bayesian" quantile-based pattern classification. - Fatemeh Mahmoudi; Mostafa Razmkhah; B. John Oommen (Pattern Anal. Appl., 2021)

On utilizing 2D features from 3D scans to enhance the prediction of lung cancer survival rates. - Tahira Ghani; B. John Oommen (Pattern Recognit. Lett., 2021)

Achieving Fair Load Balancing by Invoking a Learning Automata-Based Two-Time-Scale Separation Paradigm. - Anis Yazidi; Ismail Hassan; Hugo Lewi Hammer; B. John Oommen (IEEE Trans. Neural Networks Learn. Syst., 2021)

Enhancing the Speed of Hierarchical Learning Automata by Ordering the Actions - A Pioneering Approach. - Rebekka Olsson Omslandseter; Lei Jiao 001; B. John Oommen (AI, 2022)

The Hierarchical Discrete Learning Automaton Suitable for Environments with Many Actions and High Accuracy Requirements. - Rebekka Olsson Omslandseter; Lei Jiao 001; Xuan Zhang 007; Anis Yazidi; B. John Oommen (AI, 2022)

A Comprehensive Survey of Estimator Learning Automata and Their Recent Convergence Results. - B. John Oommen; Xuan Zhang 007; Lei Jiao 001 (Honoring Professor Mohammad S. Obaidat, 2022)

Learning Automata with Artificial Reflecting Barriers in Games with Limited Information. - Ismail Hassan; B. John Oommen; Anis Yazidi (FLAIRS, 2022)

Machine Learning and AI Approaches for Classifying Primary Brain Tumours Using Conventional MRI Scans. - Nitya Kuruvila; Tahira Ghani; Omar Islam; B. John Oommen (MICAD, 2023)

Adaptive learning with artificial barriers yielding Nash equilibria in general games. - Ismail Hassan; B. John Oommen; Anis Yazidi (Knowl. Eng. Rev., 2023)

User grouping and power allocation in NOMA systems: a novel semi-supervised reinforcement learning-based solution. - Rebekka Olsson Omslandseter; Lei Jiao 001; Yuanwei Liu; B. John Oommen (Pattern Anal. Appl., 2023)

Solving Two-Person Zero-Sum Stochastic Games With Incomplete Information Using Learning Automata With Artificial Barriers. - Anis Yazidi; Daniel Silvestre; B. John Oommen (IEEE Trans. Neural Networks Learn. Syst., 2023)

Learning automata-based partitioning algorithms for stochastic grouping problems with non-equal partition sizes. - B. John Oommen; Rebekka Olsson Omslandseter; Lei Jiao 001 (Pattern Anal. Appl., 2023)

The object migration automata: its field, scope, applications, and future research challenges. - B. John Oommen; Rebekka Olsson Omslandseter; Lei Jiao 001 (Pattern Anal. Appl., 2023)

Pioneering approaches for enhancing the speed of hierarchical LA by ordering the actions. - Rebekka Olsson Omslandseter; Lei Jiao 001; B. John Oommen (Inf. Sci., 2023)

The Hierarchical Discrete Pursuit Learning Automaton: A Novel Scheme With Fast Convergence and Epsilon-Optimality. - Rebekka Olsson Omslandseter; Lei Jiao 001; Xuan Zhang 007; Anis Yazidi; B. John Oommen (IEEE Trans. Neural Networks Learn. Syst., 2024)