B. John Oommen

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2012
221The entire range of Chaotic pattern recognition properties possessed by the Adachi neural network. Ke Qin, B. John Oommen. Intelligent Decision Technologies (6): 27-41 (2012). Web SearchBibTeXDownload
220On using prototype reduction schemes to optimize locally linear reconstruction methods. Sang-Woon Kim, B. John Oommen. Pattern Recognition (45): 498-511 (2012). Web SearchBibTeXDownload
2011
219A New Frontier in Novelty Detection: Pattern Recognition of Stochastically Episodic Events. Colin Bellinger, B. John Oommen. ACIIDS (1) 2011, 435-444. Web SearchBibTeXDownload
218Anomaly Detection in Dynamic Systems Using Weak Estimators. Justin Zhan, B. John Oommen, Johanna Crisostomo. ACM Trans. Internet Techn. (11): 3 (2011). Web SearchBibTeXDownload
217Tracking the Preferences of Users Using Weak Estimators. Anis Yazidi, Ole-Christoffer Granmo, B. John Oommen. Australasian Conference on Artificial Intelligence 2011, 799-808. Web SearchBibTeXDownload
216Semi-Supervised Classification Using Tree-Based Self-Organizing Maps. César A. Astudillo, B. John Oommen. Australasian Conference on Artificial Intelligence 2011, 21-30. Web SearchBibTeXDownload
215On 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, 1553-1558. Web SearchBibTeXDownload
214Generalized Bayesian Pursuit: A Novel Scheme for Multi-Armed Bernoulli Bandit Problems. Xuan Zhang, B. John Oommen, Ole-Christoffer Granmo. EANN/AIAI (2) 2011, 122-131. Web SearchBibTeXDownload
213Learning automata-based solutions to the optimal web polling problem modelled as a nonlinear fractional knapsack problem. Ole-Christoffer Granmo, B. John Oommen. Eng. Appl. of AI (24): 1238-1251 (2011). Web SearchBibTeXDownload
212A 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, 11-21. Web SearchBibTeXDownload
211Using Artificial Intelligence Techniques for Strategy Generation in the Commons Game. Petro Verkhogliad, B. John Oommen. HAIS (1) 2011, 43-50. Web SearchBibTeXDownload
210The Bayesian Pursuit Algorithm: A New Family of Estimator Learning Automata. Xuan Zhang, Ole-Christoffer Granmo, B. John Oommen. IEA/AIE (2) 2011, 522-531. Web SearchBibTeXDownload
209Imposing tree-based topologies onto self organizing maps. César A. Astudillo, B. John Oommen. Inf. Sci. (181): 3798-3815 (2011). Web SearchBibTeXDownload
208On Merging the Fields of Neural Networks and Adaptive Data Structures to Yield New Pattern Recognition Methodologies. B. John Oommen. PReMI 2011, 13-16. Web SearchBibTeXDownload
2010
207Modeling a Domain in a Tutorial-like System Using Learning Automata. B. John Oommen, M. Khaled Hashem. Acta Cybern. (19): 635-653 (2010). Web SearchBibTeXDownload
206Optimal 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. (33): 3-20 (2010). Web SearchBibTeXDownload
205On Optimizing Locally Linear Nearest Neighbour Reconstructions Using Prototype Reduction Schemes. Sang-Woon Kim, B. John Oommen. Australasian Conference on Artificial Intelligence 2010, 153-163. Web SearchBibTeXDownload
204Potential AI Strategies to Solve the Commons Game: A Position Paper. Petro Verkhogliad, B. John Oommen. Canadian Conference on AI 2010, 352-356. Web SearchBibTeXDownload
203A 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, 36-44. Web SearchBibTeX
202On 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, 45-52. Web SearchBibTeX
201A Learning Automata Based Solution to Service Selection in Stochastic Environments. Anis Yazidi, Ole-Christoffer Granmo, B. John Oommen. IEA/AIE (3) 2010, 209-218. Web SearchBibTeXDownload
200Solving Multiconstraint Assignment Problems Using Learning Automata. Geir Horn, B. John Oommen. IEEE Transactions on Systems, Man, and Cybernetics, Part B (40): 6-18 (2010). Web SearchBibTeXDownload
199Modeling a Student-Classroom Interaction in a Tutorial-Like System Using Learning Automata. B. John Oommen, M. Khaled Hashem. IEEE Transactions on Systems, Man, and Cybernetics, Part B (40): 29-42 (2010). Web SearchBibTeXDownload
198Modeling a Student's Behavior in a Tutorial-Like System Using Learning Automata. B. John Oommen, M. Khaled Hashem. IEEE Transactions on Systems, Man, and Cybernetics, Part B (40): 481-492 (2010). Web SearchBibTeXDownload
197On Utilizing Association and Interaction Concepts for Enhancing Microaggregation in Secure Statistical Databases. B. John Oommen, Ebaa Fayyoumi. IEEE Transactions on Systems, Man, and Cybernetics, Part B (40): 198-207 (2010). Web SearchBibTeXDownload
196Random 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 Transactions on Systems, Man, and Cybernetics, Part B (40): 66-76 (2010). Web SearchBibTeXDownload
195Solving Stochastic Nonlinear Resource Allocation Problems Using a Hierarchy of Twofold Resource Allocation Automata. Ole-Christoffer Granmo, B. John Oommen. IEEE Trans. Computers (59): 545-560 (2010). Web SearchBibTeXDownload
194Multi-class pairwise linear dimensionality reduction using heteroscedastic schemes. Luis Rueda, B. John Oommen, Claudio Henríquez. Pattern Recognition (43): 2456-2465 (2010). Web SearchBibTeXDownload
193Peptide classification using optimal and information theoretic syntactic modeling. Eser Aygün, B. John Oommen, Zehra Cataltepe. Pattern Recognition (43): 3891-3899 (2010). Web SearchBibTeXDownload
192Learning 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, 327-338. Web SearchBibTeXDownload
191A survey on statistical disclosure control and micro-aggregation techniques for secure statistical databases. Ebaa Fayyoumi, B. John Oommen. Softw., Pract. Exper. (40): 1161-1188 (2010). Web SearchBibTeXDownload
190Language Detection and Tracking in Multilingual Documents Using Weak Estimators. Aleksander Stensby, B. John Oommen, Ole-Christoffer Granmo. SSPR/SPR 2010, 600-609. Web SearchBibTeXDownload
189On simulating episodic events against a background of noise-like non-episodic events. Colin Bellinger, B. John Oommen. SummerSim 2010, 452-460. Web SearchBibTeXDownload
188Fault-tolerant routing in adversarial mobile ad hoc networks: an efficient route estimation scheme for non-stationary environments. B. John Oommen, Sudip Misra. Telecommunication Systems (44): 159-169 (2010). Web SearchBibTeXDownload
2009
187An 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, 485-491. Web SearchBibTeXDownload
186On Using Adaptive Binary Search Trees to Enhance Self Organizing Maps. César A. Astudillo, B. John Oommen. Australasian Conference on Artificial Intelligence 2009, 199-209. Web SearchBibTeXDownload
185Anomaly Detection in Dynamic Social Systems Using Weak Estimators. Justin Zhan, B. John Oommen, Johanna Crisostomo. CSE (4) 2009, 18-25. Web SearchBibTeXDownload
184Cybernetics and Learning Automata. B. John Oommen, Sudip Misra. Handbook of Automation 2009, 221-235. Web SearchBibTeXDownload
183A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Sampling. Ole-Christoffer Granmo, B. John Oommen. IEA/AIE 2009, 523-534. Web SearchBibTeXDownload
182Adachi-Like Chaotic Neural Networks Requiring Linear-Time Computations by Enforcing a Tree-Shaped Topology. Ke Qin, B. John Oommen. IEEE Transactions on Neural Networks (20): 1797-1809 (2009). Web SearchBibTeXDownload
181Achieving Microaggregation for Secure Statistical Databases Using Fixed-Structure Partitioning-Based Learning Automata. Ebaa Fayyoumi, B. John Oommen. IEEE Transactions on Systems, Man, and Cybernetics, Part B (39): 1192-1205 (2009). Web SearchBibTeXDownload
180Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems. Ole-Christoffer Granmo, B. John Oommen. Intelligent Systems for Knowledge Management 2009, 1-30. Web SearchBibTeXDownload
179An efficient pursuit automata approach for estimating stable all-pairs shortest paths in stochastic network environments. Sudip Misra, B. John Oommen. Int. J. Communication Systems (22): 441-468 (2009). Web SearchBibTeXDownload
178Learning Automata Based Intelligent Tutorial-like System. B. John Oommen, M. Khaled Hashem. KES (1) 2009, 360-373. Web SearchBibTeXDownload
177Estimation of distributions involving unobservable events: the case of optimal search with unknown Target Distributions. Qingxin Zhu, B. John Oommen. Pattern Anal. Appl. (12): 37-53 (2009). Web SearchBibTeXDownload
176On using prototype reduction schemes to enhance the computation of volume-based inter-class overlap measures. Sang-Woon Kim, B. John Oommen. Pattern Recognition (42): 2695-2704 (2009). Web SearchBibTeXDownload
175On Utilizing Optimal and Information Theoretic Syntactic Modeling for Peptide Classification. Eser Aygün, B. John Oommen, Zehra Cataltepe. PRIB 2009, 24-35. Web SearchBibTeXDownload
2008
174Enhancing Micro-Aggregation Technique by Utilizing Dependence-Based Information in Secure Statistical Databases. B. John Oommen, Ebaa Fayyoumi. ACISP 2008, 404-418. Web SearchBibTeXDownload
173An AI-Based Causal Strategy for Securing Statistical Databases Using Micro-aggregation. B. John Oommen, Ebaa Fayyoumi. Australasian Conference on Artificial Intelligence 2008, 423-434. Web SearchBibTeXDownload
172Spikes annihilation in the Hodgkin-Huxley neuron. Dragos Calitoiu, B. John Oommen, Doron Nussbaum. Biological Cybernetics (98): 239-257 (2008). Web SearchBibTeXDownload
171A Fast Computation of Inter-class Overlap Measures Using Prototype Reduction Schemes. Sang-Woon Kim, B. John Oommen. Canadian Conference on AI 2008, 173-184. Web SearchBibTeXDownload
170Chernoff-Based Multi-class Pairwise Linear Dimensionality Reduction. Luis Rueda, Claudio Henríquez, B. John Oommen. CIARP 2008, 301-308. Web SearchBibTeXDownload
169A Hierarchy of Twofold Resource Allocation Automata Supporting Optimal Web Polling. Ole-Christoffer Granmo, B. John Oommen. IEA/AIE 2008, 347-358. Web SearchBibTeXDownload
168On Using Prototype Reduction Schemes to Optimize Kernel-Based Fisher Discriminant Analysis. Sang-Woon Kim, B. John Oommen. IEEE Transactions on Systems, Man, and Cybernetics, Part B (38): 564-570 (2008). Web SearchBibTeXDownload
167A Solution to the Stochastic Point Location Problem in Metalevel Nonstationary Environments. B. John Oommen, Sang-Woon Kim, M. T. Samuel, Ole-Christoffer Granmo. IEEE Transactions on Systems, Man, and Cybernetics, Part B (38): 466-476 (2008). Web SearchBibTeXDownload
166An efficient compression scheme for data communication which uses a new family of self-organizing binary search trees. Luis Rueda, B. John Oommen. Int. J. Communication Systems (21): 1091-1120 (2008). Web SearchBibTeXDownload
165Modeling and simulating a disease outbreak by learning a contagion parameter-based model. B. John Oommen, Dragos Calitoiu. SpringSim 2008, 547-555. Web SearchBibTeXDownload
164Large scale modeling of the piriform cortex for analyzing antiepileptic effects. Dragos Calitoiu, Doron Nussbaum, B. John Oommen. SpringSim 2008, 599-608. Web SearchBibTeXDownload
163Chaotic Pattern Recognition: The Spectrum of Properties of the Adachi Neural Network. Ke Qin, B. John Oommen. SSPR/SPR 2008, 540-550. Web SearchBibTeXDownload
2007
162The Pursuit Automaton Approach for Estimating All-Pairs Shortest Paths in Dynamically Changing Networks. Sudip Misra, B. John Oommen. AINA Workshops (1) 2007, 124-129. Web SearchBibTeXDownload
161Some Analysis on the Network of Bursting Neurons: Quantifying Behavioral Synchronization. Dragos Calitoiu, B. John Oommen, Doron Nussbaum. Australian Conference on Artificial Intelligence 2007, 110-119. Web SearchBibTeXDownload
160On 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, 36-47. Web SearchBibTeXDownload
159Numerical Results on the Hodgkin-Huxley Neural Network: Spikes Annihilation. Dragos Calitoiu, B. John Oommen, Doron Nussbaum. BVAI 2007, 378-387. Web SearchBibTeXDownload
158Analytic Results on the Hodgkin-Huxley Neural Network: Spikes Annihilation. Dragos Calitoiu, B. John Oommen, Doron Nussbaum. Canadian Conference on AI 2007, 320-331. Web SearchBibTeXDownload
157Using 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, 161-167. Web SearchBibTeXDownload
156A Novel Framework for Self-Organizing Lists in Environments with Locality of Reference: Lists-on-Lists. Abdelrahman Amer, B. John Oommen. Comput. J. (50): 186-196 (2007). Web SearchBibTeXDownload
155A Novel Method for Micro-Aggregation in Secure Statistical Databases Using Association and Interaction. B. John Oommen, Ebaa Fayyoumi. ICICS 2007, 126-140. Web SearchBibTeXDownload
154On Using Learning Automata to Model a Student's Behavior in a Tutorial-like System. M. Khaled Hashem, B. John Oommen. IEA/AIE 2007, 813-822. Web SearchBibTeXDownload
153Stochastic Point Location in Non-stationary Environments and Its Applications. B. John Oommen, Sang-Woon Kim, Mathew Samuel, Ole-Christoffer Granmo. IEA/AIE 2007, 845-854. Web SearchBibTeXDownload
152Learning 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 Transactions on Systems, Man, and Cybernetics, Part B (37): 166-175 (2007). Web SearchBibTeXDownload
151Desynchronizing a Chaotic Pattern Recognition Neural Network to Model Inaccurate Perception. Dragos Calitoiu, B. John Oommen, Doron Nussbaum. IEEE Transactions on Systems, Man, and Cybernetics, Part B (37): 692-704 (2007). Web SearchBibTeXDownload
150Routing Bandwidth-Guaranteed Paths in MPLS Traffic Engineering: A Multiple Race Track Learning Approach. B. John Oommen, Sudip Misra, Ole-Christoffer Granmo. IEEE Trans. Computers (56): 959-976 (2007). Web SearchBibTeXDownload
149Breadth-first search strategies for trie-based syntactic pattern recognition. B. John Oommen, Ghada Hany Badr. Pattern Anal. Appl. (10): 1-13 (2007). Web SearchBibTeXDownload
148Periodicity and stability issues of a chaotic pattern recognition neural network. Dragos Calitoiu, B. John Oommen, Doron Nussbaum. Pattern Anal. Appl. (10): 175-188 (2007). Web SearchBibTeXDownload
147On using prototype reduction schemes to optimize dissimilarity-based classification. Sang-Woon Kim, B. John Oommen. Pattern Recognition (40): 2946-2957 (2007). Web SearchBibTeXDownload
146On the estimation of independent binomial random variables using occurrence and sequential information. B. John Oommen, Sang-Woon Kim, Geir Horn. Pattern Recognition (40): 3263-3276 (2007). Web SearchBibTeXDownload
145Using learning automata to model the behavior of a teacher in a tutorial-like system. M. Khaled Hashem, B. John Oommen. SMC 2007, 76-82. Web SearchBibTeXDownload
144Using learning automata to model a student-classroom interaction in a tutorial-like system. M. Khaled Hashem, B. John Oommen. SMC 2007, 1177-1182. Web SearchBibTeXDownload
143Goal-oriented optimal subset selection of correlated multimedia streams. Pradeep K. Atrey, Mohan S. Kankanhalli, B. John Oommen. TOMCCAP (3) (2007). Web SearchBibTeXDownload
2006
142On Optimizing the k-Ward Micro-aggregation Technique for Secure Statistical Databases. Ebaa Fayyoumi, B. John Oommen. ACISP 2006, 324-335. Web SearchBibTeXDownload
141The averaged mappings problem: statement, applications, and approximate solution. Xavier Hilaire, B. John Oommen. ACM Southeast Regional Conference 2006, 24-29. Web SearchBibTeXDownload
140Turning Lights Out with DQ-Learning. Denis V. Batalov, B. John Oommen. Artificial Intelligence and Applications 2006, 451-456. Web SearchBibTeX
139Empirical 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, 1252-1258. Web SearchBibTeXDownload
138On Utilizing Attribute Cardinality Maps to Enhance Query Optimization in the Oracle Database System. B. John Oommen, Jing Chen. ICEIS (1) 2006, 23-35. Web SearchBibTeX
137On Enhancing Query Optimization in the Oracle Database System by Utilizing Attribute Cardinality Maps. B. John Oommen, Jing Chen. ICEIS (Selected Papers) 2006, 38-71. Web SearchBibTeXDownload
136On Optimizing Dissimilarity-Based Classification Using Prototype Reduction Schemes. Sang-Woon Kim, B. John Oommen. ICIAR (1) 2006, 15-28. Web SearchBibTeXDownload
135An Efficient Dynamic Algorithm for Maintaining All-Pairs Shortest Paths in Stochastic Networks. Sudip Misra, B. John Oommen. IEEE Trans. Computers (55): 686-702 (2006). Web SearchBibTeXDownload
134A Stochastic Random-Races Algorithm for Routing in MPLS Traffic Engineering. B. John Oommen, Sudip Misra, Ole-Christoffer Granmo. INFOCOM 2006. Web SearchBibTeXDownload
133A fast and efficient nearly-optimal adaptive Fano coding scheme. Luis Rueda, B. John Oommen. Inf. Sci. (176): 1656-1683 (2006). Web SearchBibTeXDownload
132A novel look-ahead optimization strategy for trie-based approximate string matching. Ghada Badr, B. John Oommen. Pattern Anal. Appl. (9): 177-187 (2006). Web SearchBibTeXDownload
131Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments. B. John Oommen, Luis Rueda. Pattern Recognition (39): 328-341 (2006). Web SearchBibTeXDownload
130Prototype reduction schemes applicable for non-stationary data sets. Sang-Woon Kim, B. John Oommen. Pattern Recognition (39): 209-222 (2006). Web SearchBibTeXDownload
129A Fixed Structure Learning Automaton Micro-aggregation Technique for Secure Statistical Databases. Ebaa Fayyoumi, B. John Oommen. Privacy in Statistical Databases 2006, 114-128. Web SearchBibTeXDownload
128On the Theory and Applications of Sequence Based Estimation of Independent Binomial Random Variables. B. John Oommen, Sang-Woon Kim, Geir Horn. SSPR/SPR 2006, 8-21. Web SearchBibTeXDownload
127On Optimizing Kernel-Based Fisher Discriminant Analysis Using Prototype Reduction Schemes. Sang-Woon Kim, B. John Oommen. SSPR/SPR 2006, 826-834. Web SearchBibTeXDownload
126Lists on Lists: A Framework for Self-organizing Lists in Environments with Locality of Reference. Abdelrahman Amer, B. John Oommen. WEA 2006, 109-120. Web SearchBibTeXDownload
125A Fault-Tolerant Routing Algorithm for Mobile Ad Hoc Networks Using a Stochastic Learning-Based Weak Estimation Procedure. B. John Oommen, Sudip Misra. WiMob 2006, 31-37. Web SearchBibTeXDownload
2005
124On using conditional rotations and randomized heuristics for self-organizing ternary search tries. Ghada Badr, B. John Oommen. ACM Southeast Regional Conference (1) 2005, 109-115. Web SearchBibTeXDownload
123A formal analysis of why heuristic functions work. B. John Oommen, Luís G. Rueda. Artif. Intell. (164): 1-22 (2005). Web SearchBibTeXDownload
122Time-Varying Prototype Reduction Schemes Applicable for Non-stationary Data Sets. Sang-Woon Kim, B. John Oommen. Australian Conference on Artificial Intelligence 2005, 614-623. Web SearchBibTeXDownload
121Self-Adjusting of Ternary Search Tries Using Conditional Rotations and Randomized Heuristics. Ghada Hany Badr, B. John Oommen. Comput. J. (48): 200-219 (2005). Web SearchBibTeXDownload
120A Look-Ahead Branch and Bound Pruning Scheme for Trie-Based Approximate String Matching. Ghada Badr, B. John Oommen. CORES 2005, 87-94. Web SearchBibTeXDownload
119Neural Network-Based Chaotic Pattern Recognition - Part 2: Stability and Algorithmic Issues. Dragos Calitoiu, B. John Oommen, Doron Nussbaum. CORES 2005, 3-16. Web SearchBibTeXDownload
118Enhancing Trie-Based Syntactic Pattern Recognition Using AI Heuristic Search Strategies. Ghada Badr, B. John Oommen. ICAPR (1) 2005, 1-17. Web SearchBibTeXDownload
117Dynamic algorithms for the shortest path routing problem: learning automata-based solutions. Sudip Misra, B. John Oommen. IEEE Transactions on Systems, Man, and Cybernetics, Part B (35): 1179-1192 (2005). Web SearchBibTeXDownload
116On 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. (27): 136-141 (2005). Web SearchBibTeXDownload
115On 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. (27): 455-460 (2005). Web SearchBibTeXDownload
114A Fixed-Structure Learning Automaton Solution to the Stochastic Static Mapping Problem. Geir Horn, B. John Oommen. IPDPS 2005. Web SearchBibTeXDownload
113New Algorithms for Maintaining All-Pairs Shortest Paths. Sudip Misra, B. John Oommen. ISCC 2005, 116-121. Web SearchBibTeXDownload
112Efficient Adaptive Data Compression Using Fano Binary Search Trees. Luís G. Rueda, B. John Oommen. ISCIS 2005, 768-779. Web SearchBibTeXDownload
111On Utilizing Stochastic Learning Weak Estimators for Training and Classification of Patterns with Non-stationary Distributions. B. John Oommen, Luís G. Rueda. KI 2005, 107-120. Web SearchBibTeXDownload
110Modeling Inaccurate Perception: Desynchronization Issues of a Chaotic Pattern Recognition Neural Network. Dragos Calitoiu, B. John Oommen, Dorin Nusbaumm. SCIA 2005, 821-830. Web SearchBibTeXDownload
2004
109Adaptive Algorithms for Routing and Traffic Engineering in Stochastic Networks. Sudip Misra, B. John Oommen. AAAI 2004, 993-994. Web SearchBibTeX
108Deterministic Majority filters applied to stochastic sorting. B. John Oommen, Jack R. Zgierski, Doron Nussbaum. ACM Southeast Regional Conference 2004, 228-233. Web SearchBibTeXDownload
107On Families of New Adaptive Compression Algorithms Suitable for Time-Varying Source Data. Luís G. Rueda, B. John Oommen. ADVIS 2004, 234-244. Web SearchBibTeXDownload
106Selecting Subspace Dimensions for Kernel-Based Nonlinear Subspace Classifiers Using Intelligent Search Methods. Sang-Woon Kim, B. John Oommen. Australian Conference on Artificial Intelligence 2004, 1115-1121. Web SearchBibTeXDownload
105Stochastic Learning Automata-Based Dynamic Algorithms for the Single Source Shortest Path Problem. Sudip Misra, B. John Oommen. IEA/AIE 2004, 239-248. Web SearchBibTeXDownload
104Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets. Sang-Woon Kim, B. John Oommen. IEEE Transactions on Systems, Man, and Cybernetics, Part B (34): 1384-1397 (2004). Web SearchBibTeXDownload
103A nearly-optimal Fano-based coding algorithm. Luís G. Rueda, B. John Oommen. Inf. Process. Manage. (40): 257-268 (2004). Web SearchBibTeXDownload
102A formal approach to using data distributions for building causal polytree structures. M. Ouerd, B. John Oommen, Stan Matwin. Inf. Sci. (168): 111-132 (2004). Web SearchBibTeXDownload
101GPSPA: a new adaptive algorithm for maintaining shortest path routing trees in stochastic networks. Sudip Misra, B. John Oommen. Int. J. Communication Systems (17): 963-984 (2004). Web SearchBibTeXDownload
100Generalized pursuit learning algorithms for shortest path routing tree computation. Sudip Misra, B. John Oommen. ISCC 2004, 891-896. Web SearchBibTeXDownload
99Stochastic Sorting Using Deterministic Consecutive and Leader Filters. B. John Oommen, Jack R. Zgierski, Doron Nussbaum. MSV/AMCS 2004, 399-405. Web SearchBibTeX
98On using prototype reduction schemes to optimize kernel-based nonlinear subspace methods. Sang-Woon Kim, B. John Oommen. Pattern Recognition (37): 227-239 (2004). Web SearchBibTeXDownload
97Recent Results on Learning from Stochastic Teachers and Compulsive Liars/Con-Men. B. John Oommen. PRIS 2004, 4. Web SearchBibTeX
96On Designing Pattern Classifiers Using Artificially Created Bootstrap Samples. Qun Wang, B. John Oommen. PRIS 2004, 159-168. Web SearchBibTeX
95A New Family of Weak Estimators for Training in Non-stationary Distributions. B. John Oommen, Luís G. Rueda. SSPR/SPR 2004, 644-652. Web SearchBibTeXDownload
94Dictionary-Based Syntactic Pattern Recognition Using Tries. B. John Oommen, Ghada Badr. SSPR/SPR 2004, 251-259. Web SearchBibTeXDownload
2003
93On 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, 24-40. Web SearchBibTeXDownload
92On Using Prototype Reduction Schemes and Classifier Fusion Strategies to Optimize Kernel-Based Nonlinear Subspace Methods. Sang-Woon Kim, B. John Oommen. Australian Conference on Artificial Intelligence 2003, 783-795. Web SearchBibTeXDownload
91Enhancing Caching in Distributed Databases Using Intelligent Polytree Representations. Ouerd Messaouda, B. John Oommen, Stan Matwin. Canadian Conference on AI 2003, 498-504. Web SearchBibTeXDownload
90A Kohonen-like decomposition method for the Euclidean traveling salesman problem-KNIES_DECOMPOSE. Necati Aras, I. Kuban Altinel, B. John Oommen. IEEE Transactions on Neural Networks (14): 869-890 (2003). Web SearchBibTeXDownload
89Benchmarking attribute cardinality maps for database systems using the TPC-D specifications. B. John Oommen, Murali Thiyagarajah. IEEE Transactions on Systems, Man, and Cybernetics, Part B (33): 913-924 (2003). Web SearchBibTeXDownload
88A new histogram method for sparse attributes: the averaged rectangular attribute cardinality map. B. John Oommen, Jing Chen. ISICT 2003, 119-125. Web SearchBibTeXDownload
87A brief taxonomy and ranking of creative prototype reduction schemes. Sang-Woon Kim, B. John Oommen. Pattern Anal. Appl. (6): 232-244 (2003). Web SearchBibTeXDownload
86On optimal pairwise linear classifiers for normal distributions: the d-dimensional case. Luís G. Rueda, B. John Oommen. Pattern Recognition (36): 13-23 (2003). Web SearchBibTeXDownload
85Enhancing prototype reduction schemes with LVQ3-type algorithms. Sang-Woon Kim, B. John Oommen. Pattern Recognition (36): 1083-1093 (2003). Web SearchBibTeXDownload
84Classification Error-Rate Estimation Using New Pseudo-Sample Bootstrap Methods. Qun Wang, B. John Oommen. PRIS 2003, 96-103. Web SearchBibTeX
2002
83Optimizing Kernel-Based Nonlinear Subspace Methods Using Prototype Reduction Schemes. Sang-Woon Kim, B. John Oommen. Australian Joint Conference on Artificial Intelligence 2002, 155-166. Web SearchBibTeXDownload
82The Efficiency of Histogram-like Techniques for Database Query Optimization. B. John Oommen, Luís G. Rueda. Comput. J. (45): 494-510 (2002). Web SearchBibTeXDownload
81Discretized learning automata solutions to the capacity assignment problem for prioritized networks. B. John Oommen, T. Dale Roberts. IEEE Transactions on Systems, Man, and Cybernetics, Part B (32): 821-831 (2002). Web SearchBibTeXDownload
80Generalized pursuit learning schemes: new families of continuous and discretized learning automata. M. Agache, B. John Oommen. IEEE Transactions on Systems, Man, and Cybernetics, Part B (32): 738-749 (2002). Web SearchBibTeXDownload
79On Optimal Pairwise Linear Classifiers for Normal Distributions: The Two-Dimensional Case. Luís G. Rueda, B. John Oommen. IEEE Trans. Pattern Anal. Mach. Intell. (24): 274-280 (2002). Web SearchBibTeXDownload
78Enhanced layered segment trees: a pragmatic data structure for real-time processing of geometric objects. Gopal Racherla, Sridhar Radhakrishnan, B. John Oommen. Pattern Recognition (35): 2303-2309 (2002). Web SearchBibTeXDownload
77On Utilizing LVQ3-Type Algorithms to Enhance Prototype Reduction Schemes. Sang-Woon Kim, B. John Oommen. PRIS 2002, 242-256. Web SearchBibTeX
76Using Pattern Recognition Techniques to Derive a Formal Analysis of Why Heuristics Functions Work. B. John Oommen, Luís G. Rueda. PRIS 2002, 45-58. Web SearchBibTeX
75Recursive Prototype Reduction Schemes Applicable for Large Data Sets. Sang-Woon Kim, B. John Oommen. SSPR/SPR 2002, 528-537. Web SearchBibTeXDownload
2001
74Resolving Minsky's Paradox: The d-Dimensional Normal Distribution Case. Luís G. Rueda, B. John Oommen. Australian Joint Conference on Artificial Intelligence 2001, 25-36. Web SearchBibTeXDownload
73Histogram Methods in Query Optimization: The Relation between Accuracy and Optimality. B. John Oommen, Luís G. Rueda. DASFAA 2001, 320-326. Web SearchBibTeX
72A 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, 212-221. Web SearchBibTeXDownload
71Continuous and discretized pursuit learning schemes: various algorithms and their comparison. B. John Oommen, M. Agache. IEEE Transactions on Systems, Man, and Cybernetics, Part B (31): 277-287 (2001). Web SearchBibTeXDownload
70On the Pattern Recognition of Noisy Subsequence Trees. B. John Oommen, R. K. S. Loke. IEEE Trans. Pattern Anal. Mach. Intell. (23): 929-946 (2001). Web SearchBibTeXDownload
69Distance Bias Adjustment Bootstrap Estimation for Bhattacharyya Error Bound in Classifiers. B. John Oommen, Qun Wang. PRIS 2001, 103-117. Web SearchBibTeX
2000
68A Kohonen-like Decomposition Method for the Traveling Salesman Problem: KNIESDECOMPOSE. Necati Aras, I. Kuban Altinel, B. John Oommen. ECAI 2000, 261-265. Web SearchBibTeX
67An Empirical Comparison of Histogram-Like Techniques for Query Optimization. B. John Oommen, Luis Rueda. ICEIS 2000, 71-78. Web SearchBibTeX
66Query Result Size Estimation Using the Trapezoidal Attribute Cardinality Map. B. John Oommen, Murali Thiyagarajah. IDEAS 2000, 236-242. Web SearchBibTeXDownload
65Continuous Learning Automata Solutions to the Capacity Assignment Problem. B. John Oommen, T. Dale Roberts. IEEE Trans. Computers (49): 608-620 (2000). Web SearchBibTeXDownload
64A Formalism for Building Causal Polytree Structures Using Data Distributions. M. Ouerd, B. John Oommen, Stan Matwin. ISMIS 2000, 629-637. Web SearchBibTeXDownload
63The Foundational Theory of Optimal Bayesian Pairwise Linear Classifiers. Luis Rueda, B. John Oommen. SSPR/SPR 2000, 581-590. Web SearchBibTeXDownload
1999
62On Benchmarking Attribute Cardinality Maps for Database Systems Using the TPC-D Specification. Murali Thiyagarajah, B. John Oommen. DEXA 1999, 292-301. Web SearchBibTeXDownload
61Prototype Validation of the Trapezoidal Attribute Cardinality Map for Query Optimization in Database Systems. Murali Thiyagarajah, B. John Oommen. ICEIS 1999, 156-162. Web SearchBibTeX
60Query Result Size Estimation Using a Novel Histogram-like Technique: The Rectangular Attribute Cardinality Map. B. John Oommen, Murali Thiyagarajah. IDEAS 1999, 3-15. Web SearchBibTeXDownload
59On Solving the Capacity Assignment Problem Using Continous Learning Automata. B. John Oommen, T. Dale Roberts. IEA/AIE 1999, 622-631. Web SearchBibTeXDownload
58Designing syntactic pattern classifiers using vector quantization and parametric string editing. B. John Oommen, R. K. S. Loke. IEEE Transactions on Systems, Man, and Cybernetics, Part B (29): 881-888 (1999). Web SearchBibTeXDownload
57The Kohonen network incorporating explicit statistics and its application to the travelling salesman problem. Necati Aras, B. John Oommen, I. Kuban Altinel. Neural Networks (12): 1273-1284 (1999). Web SearchBibTeXDownload
1998
56A Fast Efficient Solution to the Capacity Assignment Problem Using Discretized Learning Automata. B. John Oommen, T. Dale Roberts. IEA/AIE (Vol. 2) 1998, 56-65. Web SearchBibTeXDownload
55Automata learning and intelligent tertiary searching for stochastic point location. B. John Oommen, Govindachari Raghunath. IEEE Transactions on Systems, Man, and Cybernetics, Part B (28): 947-954 (1998). Web SearchBibTeXDownload
54Discrete vector quantization for arbitrary distance function estimation. B. John Oommen, I. Kuban Altinel, Necati Aras. IEEE Transactions on Systems, Man, and Cybernetics, Part B (28): 496-510 (1998). Web SearchBibTeXDownload
53A formal theory for optimal and information theoretic syntactic pattern recognition. B. John Oommen, Rangasami L. Kashyap. Pattern Recognition (31): 1159-1177 (1998). Web SearchBibTeXDownload
52The Noisy Subsequence Tree Recognition Problem. B. John Oommen, R. K. S. Loke. SSPR/SPR 1998, 169-180. Web SearchBibTeXDownload
1997
51Stochastic searching on the line and its applications to parameter learning in nonlinear optimization. B. John Oommen. IEEE Transactions on Systems, Man, and Cybernetics, Part B (27): 733-739 (1997). Web SearchBibTeXDownload
50String taxonomy using learning automata. B. John Oommen, Edward V. de St. Croix. IEEE Transactions on Systems, Man, and Cybernetics, Part B (27): 354-365 (1997). Web SearchBibTeXDownload
49Moment-Preserving Piecewise Linear Approximations of Signals and Images. Thai B. Nguyen, B. John Oommen. IEEE Trans. Pattern Anal. Mach. Intell. (19): 84-91 (1997). Web SearchBibTeXDownload
48Vector Quantization for Arbitrary Distance Function Estimation. I. Kuban Altinel, B. John Oommen, Necati Aras. INFORMS Journal on Computing (9): 439-451 (1997). Web SearchBibTeXDownload
47Generalized Swap-with-Parent Schemes for Self-Organizing Sequential Linear Lists. B. John Oommen, Juan Dong. ISAAC 1997, 414-423. Web SearchBibTeXDownload
46Pattern recognition of strings with substitutions, insertions, deletions and generalized transpositions. B. John Oommen, Richard K. S. Loke. Pattern Recognition (30): 789-800 (1997). Web SearchBibTeXDownload
45On the Optimal Search Problem: The Case when the Target Distribution is Unknown. Qingxin Zhu, B. John Oommen. SCCC 1997, 268-277. Web SearchBibTeXDownload
1996
44Optimal and Information Theoretic Syntactic Pattern Recognition Involving Traditional and Transposition Errors. B. John Oommen, R. K. S. Loke. FSTTCS 1996, 224-237. Web SearchBibTeXDownload
43Graph Partitioning Using Learning Automata. B. John Oommen, Edward V. de St. Croix. IEEE Trans. Computers (45): 195-208 (1996). Web SearchBibTeXDownload
42Numerical Similarity and Dissimilarity Measures Between Two Trees. B. John Oommen, K. Zhang, William Lee. IEEE Trans. Computers (45): 1426-1434 (1996). Web SearchBibTeXDownload
41The Normalized String Editing Problem Revisited. B. John Oommen, K. Zhang. IEEE Trans. Pattern Anal. Mach. Intell. (18): 669-672 (1996). Web SearchBibTeXDownload
40Optimal and Information Theoretic Syntactic Pattern Recognition for Traditional Errors. B. John Oommen, Rangasami L. Kashyap. SSPR 1996, 11-20. Web SearchBibTeXDownload
1995
39Noisy Subsequence Recognition Using Constrained String Editing Involving Substitutions, Insertions, Deletions and Generalized Transpositions. B. John Oommen, R. K. S. Loke. ICSC 1995, 116-123. Web SearchBibTeXDownload
38String Alignment with Substitution, Insertion, Deletion, Squashing and Expansion Operations. B. John Oommen. Inf. Sci. (83): 89-107 (1995). Web SearchBibTeXDownload
37On Using Learning Automata for Fast Graph Partitioning. B. John Oommen, Edward V. de St. Croix. LATIN 1995, 449-460. Web SearchBibTeXDownload
1994
36A New Technique for Enhancing Linked-List Data Retrieval: Reorganize Data Using Artificially synthesized Queries. B. John Oommen, David T. H. Ng. Comput. J. (37): 598-609 (1994). Web SearchBibTeXDownload
35Constrained Tree Editing. B. John Oommen, William Lee. Inf. Sci. (77): 253-273 (1994). Web SearchBibTeXDownload
1993
34Fast Learning Automaton-Based Image Examination and Retrieval. B. John Oommen, Chris Fothergill. Comput. J. (36): 542-553 (1993). Web SearchBibTeXDownload
33Transforming Ill-Conditioned Constrained Problems using Projections. B. John Oommen. Comput. J. (36): 282-285 (1993). Web SearchBibTeXDownload
32Adaptive Structuring of Binary Search Trees Using Conditional Rotations. Robert P. Cheetham, B. John Oommen, David T. H. Ng. IEEE Trans. Knowl. Data Eng. (5): 695-704 (1993). Web SearchBibTeXDownload
31Breaking Substitution Cyphers Using Stochastic Automata. B. John Oommen, Jack R. Zgierski. IEEE Trans. Pattern Anal. Mach. Intell. (15): 185-192 (1993). Web SearchBibTeXDownload
30Self-Organizing Doubly-Linked Lists. Radhakrishna S. Valiveti, B. John Oommen. J. Algorithms (14): 88-114 (1993). Web SearchBibTeXDownload
29Determining stochastic dependence for normally distributed vectors using the chi-squared metric. Radhakrishna S. Valiveti, B. John Oommen. Pattern Recognition (26): 975-987 (1993). Web SearchBibTeXDownload
28An Optimal Absorbing List Organization Strategy with Constant Memory Requirements. B. John Oommen, David T. H. Ng. Theor. Comput. Sci. (119): 355-361 (1993). Web SearchBibTeXDownload
1992
27A Short Note on Doubly-Linked List Reorganizing Heuristics. David T. H. Ng, B. John Oommen. Comput. J. (35): 533-535 (1992). Web SearchBibTeXDownload
26On the problem of multiple mobile robots cluttering a workspace. B. John Oommen, I. Reichstein. Inf. Sci. (63): 55-85 (1992). Web SearchBibTeXDownload
25On using the chi-squared metric for determining stochastic dependence. Radhakrishna S. Valiveti, B. John Oommen. Pattern Recognition (25): 1389-1400 (1992). Web SearchBibTeXDownload
1991
24Adaptive Linear List Reorganization for a System Processing Set Queries. Radhakrishna S. Valiveti, B. John Oommen, Jack R. Zgierski. FCT 1991, 405-414. Web SearchBibTeXDownload
23Recognizing Sources of Random Strings. Radhakrishna S. Valiveti, B. John Oommen. IEEE Trans. Pattern Anal. Mach. Intell. (13): 386-394 (1991). Web SearchBibTeXDownload
1990
22On Generating Random Permutations with Arbitrary Distributions. B. John Oommen, David T. H. Ng. Comput. J. (33): 368-374 (1990). Web SearchBibTeXDownload
21A Fast Learning Automaton Solution to the Keyboard Optimization Problem. B. John Oommen, Radhakrishna S. Valiveti, Jack R. Zgierski. IEA/AIE (Vol. 2) 1990, 981-990. Web SearchBibTeXDownload
20Deterministic Optimal and Expedient Move-to-Rear List Organizing Strategies. B. John Oommen, E. R. Hansen, J. Ian Munro. Theor. Comput. Sci. (74): 183-197 (1990). Web SearchBibTeXDownload
1989
19On Generating Random Permutations with Arbitrary Distributions. B. John Oommen, David T. H. Ng. ACM Conference on Computer Science 1989, 27-32. Web SearchBibTeX
18Generalizing Singly-Linked List Reorganizing Heuristics for Doubly-Linked Lists. David T. H. Ng, B. John Oommen. MFCS 1989, 380-389. Web SearchBibTeXDownload
17Optimal Constant Space Move-to-Rear List Organization. B. John Oommen, David T. H. Ng. Optimal Algorithms 1989, 115-125. Web SearchBibTeXDownload
1988
16On Using Conditional Rotation Operations to Adaptively Structure Binary Search Trees. Robert P. Cheetham, B. John Oommen, David T. H. Ng. ICDT 1988, 161-175. Web SearchBibTeXDownload
15Deterministic Learning Automata Solutions to the Equipartitioning Problem. B. John Oommen, Daniel C. Y. Ma. IEEE Trans. Computers (37): 2-13 (1988). Web SearchBibTeXDownload
14Correction to "Recognition of Noisy Subsequences Using Constrained Edit Distances". B. John Oommen. IEEE Trans. Pattern Anal. Mach. Intell. (10): 983-984 (1988). Web SearchBibTeXDownload
1987
13Recognition of Noisy Subsequences Using Constrained Edit Distances. B. John Oommen. IEEE Trans. Pattern Anal. Mach. Intell. (9): 676-685 (1987). Web SearchBibTeXDownload
12List Organizing Strategies Using Stochastic Move-to-Front and Stochastic Move-to-Rear Operations. B. John Oommen, E. R. Hansen. SIAM J. Comput. (16): 705-716 (1987). Web SearchBibTeXDownload
11Fast Object Partitioning Using Stochastic Learning Automata. B. John Oommen, Daniel C. Y. Ma. SIGIR 1987, 111-122. Web SearchBibTeX
1986
10Robot 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, 1101-1106. Web SearchBibTeX
9Expedient Stochastic Move-to-Front and optimal Move-to-Rear List Organizing Strategies. B. John Oommen, E. R. Hansen. ICDT 1986, 349-364. Web SearchBibTeXDownload
8Constrained string editing. B. John Oommen. Inf. Sci. (40): 267-284 (1986). Web SearchBibTeXDownload
1985
7On the Futility of Arbitrarily Increasing Memory Capabilities of Stochastic Learning Automata. B. John Oommen. CAIA 1985, 308-312. Web SearchBibTeX
6Multiaction learning automata possessing ergodicity of the mean. B. John Oommen, M. A. L. Thathachar. Inf. Sci. (35): 183-198 (1985). Web SearchBibTeXDownload
1984
5Algorithms for String Editing which Permit Arbitrarily Complex Editing Constraints. B. John Oommen. MFCS 1984, 443-451. Web SearchBibTeXDownload
1983
4Scale Preserving Smoothing of Polygons. Rangasami L. Kashyap, B. John Oommen. IEEE Trans. Pattern Anal. Mach. Intell. (5): 667-671 (1983). Web SearchBibTeXDownload
3The Noisy Substring Matching Problem. Rangasami L. Kashyap, B. John Oommen. IEEE Trans. Software Eng. (9): 365-370 (1983). Web SearchBibTeXDownload
1981
2An 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. (23): 201-217 (1981). Web SearchBibTeXDownload
1An 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. (23): 123-142 (1981). Web SearchBibTeXDownload
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