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Note: Links lead to the DBLP on the Web. Vasant Honavar Jyotishman Pathak , Yong Jiang , Vasant Honavar, James D. McCalley : Condition Data Aggregation with Application to Failure Rate Calculation of Power Transformers. HICSS 2006 Jyotishman Pathak , Samik Basu , Robyn R. Lutz , Vasant Honavar: MoSCoE: A Framework for Modeling Web Service Composition and Execution. ICDE Workshops 2006 : 143 Dae-Ki Kang , Adrian Silvescu , Vasant Honavar: RNBL-MN: A Recursive Naive Bayes Learner for Sequence Classification. PAKDD 2006 : 45-54 Flavian Vasile , Adrian Silvescu , Dae-Ki Kang , Vasant Honavar: TRIPPER: Rule Learning Using Taxonomies. PAKDD 2006 : 55-59 Jun Zhang , Dae-Ki Kang , Adrian Silvescu , Vasant Honavar: Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data. Knowl. Inf. Syst. 9 (2): 157-179 (2006) Cornelia Caragea , Doina Caragea , Vasant Honavar: Learning Support Vector Machines from Distributed Data Sources. AAAI 2005 : 1602-1603 Doina Caragea , Jun Zhang , Jie Bao , Jyotishman Pathak , Vasant Honavar: Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. ALT 2005 : 13-44 Doina Caragea , Jie Bao , Jyotishman Pathak , Adrian Silvescu , Carson M. Andorf , Drena Dobbs , Vasant Honavar: Information Integration from Semantically Heterogeneous Biological Data Sources. DEXA Workshops 2005 : 580-584 Doina Caragea , Jyotishman Pathak , Jie Bao , Adrian Silvescu , Carson M. Andorf , Drena Dobbs , Vasant Honavar: Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources. DILS 2005 : 175-190 Doina Caragea , Jun Zhang , Jie Bao , Jyotishman Pathak , Vasant Honavar: Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. Discovery Science 2005 : 14 Jun Zhang , Doina Caragea , Vasant Honavar: Learning Ontology-Aware Classifiers. Discovery Science 2005 : 308-321 Oksana Yakhnenko , Adrian Silvescu , Vasant Honavar: Discriminatively Trained Markov Model for Sequence Classification. ICDM 2005 : 498-505 Dae-Ki Kang , Doug Fuller , Vasant Honavar: Learning Classifiers for Misuse Detection Using a Bag of System Calls Representation. ISI 2005 : 511-516 Dae-Ki Kang , Jun Zhang , Adrian Silvescu , Vasant Honavar: Multinomial Event Model Based Abstraction for Sequence and Text Classification. SARA 2005 : 134-148 Feihong Wu , Jun Zhang , Vasant Honavar: Learning Classifiers Using Hierarchically Structured Class Taxonomies. SARA 2005 : 313-320 Jyotishman Pathak , Neeraj Koul , Doina Caragea , Vasant Honavar: A framework for semantic web services discovery. WIDM 2005 : 45-50 Doina Caragea , Jyotishman Pathak , Vasant Honavar: Learning Classifiers from Semantically Heterogeneous Data. CoopIS/DOA/ODBASE (2) 2004 : 963-980 Jinu Joo , Jun Zhang , Jihoon Yang , Vasant Honavar: Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data. Discovery Science 2004 : 347-354 Dae-Ki Kang , Adrian Silvescu , Jun Zhang , Vasant Honavar: Generation of Attribute Value Taxonomies from Data for Data-Driven Construction of Accurate and Compact Classifiers. ICDM 2004 : 130-137 Jun Zhang , Vasant Honavar: AVT-NBL: An Algorithm for Learning Compact and Accurate Naïve Bayes Classifiers from Attribute Value Taxonomies and Data. ICDM 2004 : 289-296 Jie Bao , Yu Cao , Wallapak Tavanapong , Vasant Honavar: Integration of Domain-Specific and Domain-Independent Ontologies for Colonoscopy Video Database Annotation. IKE 2004 : 82-90 Changhui Yan , Drena Dobbs , Vasant Honavar: A two-stage classifier for identification of protein-protein interface residues. ISMB/ECCB (Supplement of Bioinformatics) 2004 : 371-378 Jyotishman Pathak , Doina Caragea , Vasant Honavar: Ontology-Extended Component-Based Workflows : A Framework for Constructing Complex Workflows from Semantically Heterogeneous Software Components. SWDB 2004 : 41-56 Taner Z. Sen , Andrzej Kloczkowski , Robert L. Jernigan , Changhui Yan , Vasant Honavar, Kai-Ming Ho , Cai-Zhuang Wang , Yungok Ihm , Haibo Cao , Xun Gu , Drena Dobbs : Predicting binding sites of hydrolase-inhibitor complexes by combining several methods. BMC Bioinformatics 5 : 205 (2004) Doina Caragea , Adrian Silvescu , Vasant Honavar: A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees. Int. J. Hybrid Intell. Syst. 1 (2): 80-89 (2004) Changhui Yan , Vasant Honavar, Drena Dobbs : Identification of interface residues in protease-inhibitor and antigen-antibody complexes: a support vector machine approach. Neural Computing and Applications 13 (2): 123-129 (2004) Doina Caragea , Dianne Cook , Vasant Honavar: Towards Simple, Easy-to-Understand, yet Accurate Classifiers. ICDM 2003 : 497-500 Jun Zhang , Vasant Honavar: Learning from Attribute Value Taxonomies and Partially Specified Instances. ICML 2003 : 880-887 Doina Caragea , Jaime Reinoso , Adrian Silvescu , Vasant Honavar: Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources. IIWeb 2003 : 99-104 Anna Atramentov , Hector Leiva , Vasant Honavar: A Multi-relational Decision Tree Learning Algorithm - Implementation and Experiments. ILP 2003 : 38-56 Jaime Reinoso , Adrian Silvescu , Doina Caragea , Jyotishman Pathak , Vasant Honavar: Information Extraction and Integration from Heterogeneous, Distributed, Autonomous Information Sources : A Federated Ontology-Driven Query-Centric Approach. IRI 2003 : 183-191 Doina Caragea , Adrian Silvescu , Vasant Honavar: Learning Decision Trees form Distributed Heterogeneous Autonomous Data. MAICS 2003 : 10-17 Xiangyun Wang , Diane Schroeder , Drena Dobbs , Vasant Honavar: Automated data-driven discovery of motif-based protein function classifiers. Inf. Sci. 155 (1-2): 1-18 (2003) Guy G. Helmer , Johnny S. Wong , Vasant Honavar, Les Miller , Yanxin Wang : Lightweight agents for intrusion detection. Journal of Systems and Software 67 (2): 109-122 (2003) H. John Caulfield , Shu-Heng Chen , Heng-Da Cheng , Richard J. Duro , Vasant Honavar, Etienne E. Kerre , Mi Lu , Manuel Grana Romay , Timothy K. Shih , Dan Ventura , Paul P. Wang , Yuanyuan Yang : Proceedings of the 6th Joint Conference on Information Science, March 8-13, 2002, Research Triangle Park, North Carolina, USA JCIS / Association for Intelligent Machinery, Inc. 2002 William B. Langdon , Erick Cantú-Paz , Keith E. Mathias , Rajkumar Roy , David Davis , Riccardo Poli , Karthik Balakrishnan , Vasant Honavar, Günter Rudolph , Joachim Wegener , Larry Bull , Mitchell A. Potter , Alan C. Schultz , Julian F. Miller , Edmund K. Burke , Natasa Jonoska : GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, New York, USA, 9-13 July 2002 Morgan Kaufmann 2002 Xiangyun Wang , Diane Schroeder , Drena Dobbs , Vasant Honavar: Data-Driven Discovery of Protein Function Classifiers: Decision Trees Based on MEME Motifs outperform PROSITE Patterns and Profiles on Peptidase Families. JCIS 2002 : 1193-1199 Carson M. Andorf , Drena Dobbs , Vasant Honavar: Discovering Protein Function Classification Rules from Reduced Alphabet Representations of Protein Sequences. JCIS 2002 : 1200-1206 Jun Zhang , Adrian Silvescu , Vasant Honavar: Ontology-Driven Induction of Decision Trees at Multiple Levels of Abstraction. SARA 2002 : 316-323 Guy G. Helmer , Johnny S. Wong , Vasant Honavar, Les Miller : Automated discovery of concise predictive rules for intrusion detection. Journal of Systems and Software 60 (3): 165-175 (2002) Guy G. Helmer , Johnny S. Wong , Mark Slagell , Vasant Honavar, Les Miller , Robyn R. Lutz : A Software Fault Tree Approach to Requirements Analysis of an Intrusion Detection System. Requir. Eng. 7 (4): 207-220 (2002) Doina Caragea , Adrian Silvescu , Vasant Honavar: Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources. Emergent Neural Computational Architectures Based on Neuroscience 2001 : 547-559 Doina Caragea , Dianne Cook , Vasant Honavar: Gaining insights into support vector machine pattern classifiers using projection-based tour methods. KDD 2001 : 251-256 Robi Polikar , L. Upda , S. S. Upda , Vasant Honavar: Learn++: an incremental learning algorithm for supervised neural networks. IEEE Transactions on Systems, Man, and Cybernetics, Part C 31 (4): 497-508 (2001) Johnny Wong , Guy G. Helmer , Venkatraman Naganathan , Sriniwas Polavarapu , Vasant Honavar, Les Miller : SMART mobile agent facility. Journal of Systems and Software 56 (1): 9-22 (2001) Armin R. Mikler , Vasant Honavar, Johnny S. Wong : Autonomous agents for coordinated distributed parameterized heuristic routing in large dynamic communication networks. Journal of Systems and Software 56 (3): 231-246 (2001) Vasant Honavar, Colin de la Higuera : Introduction. Machine Learning 44 (1/2): 5-7 (2001) Rajesh Parekh , Vasant Honavar: Learning DFA from Simple Examples. Machine Learning 44 (1/2): 9-35 (2001) Doina Caragea , Adrian Silvescu , Vasant Honavar: Incremental and Distributed Learning with Support Vector Machines. AAAI/IAAI 2000 : 1067 Rajesh Parekh , Vasant Honavar: On the Relationship between Models for Learning in Helpful Environments. ICGI 2000 : 207-220 Mokdong Chug , Vasant Honavar: A Negotiation Model in Agent-mediated Electronic Commerce. ISMSE 2000 : 403-410 Wolfgang Banzhaf , Jason M. Daida , A. E. Eiben , Max H. Garzon , Vasant Honavar, Mark J. Jakiela , Robert E. Smith : Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 1999), 13-17 July 1999, Orlando, Florida, USA Morgan Kaufmann 1999 Guy G. Helmer , Johnny S. Wong , Vasant Honavar, Les Miller : Feature Selection Using a Genetic Algorithm for Intrusion Detection. GECCO 1999 : 1781 Rajesh Parekh , Vasant Honavar: Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples. ICML 1999 : 298-306 Jihoon Yang , Rajesh Parekh , Vasant Honavar, Drena Dobbs : Data-Driven Theory Refinement Using KBDistAl . IDA 1999 : 331-342 Jihoon Yang , Rajesh Parekh , Vasant Honavar: DistAl: An inter-pattern distance-based constructive learning algorithm. Intell. Data Anal. 3 (1): 55-73 (1999) Vasant Honavar, Giora Slutzki : Grammatical Inference, 4th International Colloquium, ICGI-98, Ames, Iowa, USA, July 12-14, 1998, Proceedings Springer 1998 Rajesh Parekh , Codrin M. Nichitiu , Vasant Honavar: A Polynominal Time Incremental Algorithm for Learning DFA. ICGI 1998 : 37-49 Jihoon Yang , Vasant Honavar: Feature Subset Selection Using a Genetic Algorithm. IEEE Intelligent Systems 13 (2): 44-49 (1998) Armin R. Mikler , Johnny S. K. Wong , Vasant Honavar: An object oriented approach to simulating large communication networks. Journal of Systems and Software 40 (2): 151-164 (1998) Rajesh Parekh , Vasant Honavar: Learning DFA from Simple Examples. ALT 1997 : 116-131 Armin R. Mikler , Johnny S. Wong , Vasant Honavar: Quo Vadis - A Framework for Intelligent Routing in Large Communication Networks. Journal of Systems and Software 37 (1): 61-73 (1997) Armin R. Mikler , Vasant Honavar, Johnny S. Wong : Analysis of Utility-Theoretic Heuristics for Intelligent Adaptive Network Routing. AAAI/IAAI, Vol. 1 1996 : 96-101 Karthik Balakrishnan , Vasant Honavar: Experiments in Evolutionary Synthesis of Robotic Neurocontrollers. AAAI/IAAI, Vol. 2 1996 : 1378 Rajesh Parekh , Vasant Honavar: An Incremental Interactive Algorithm for Regular Grammar Inference. AAAI/IAAI, Vol. 2 1996 : 1397 Rajesh Parekh , Jihoon Yang , Vasant Honavar: Constructive Neural Network Learning Algorithms. AAAI/IAAI, Vol. 2 1996 : 1398 Rajesh Parekh , Vasant Honavar: An incremental interactive algorithm for grammar inference. ICGI 1996 : 238-249 Chun-Hsien Chen , Vasant Honavar: A Neural Architecture for Content as well as Address-based Storage and Recall: Theory and Applications. Connect. Sci. 7 (3-4): 281-300 (1995) Vasant Honavar, Leonard Uhr : Generative learning structures and processes for generalized connectionist networks. Inf. Sci. 70 (1-2): 75-108 (1993) Vasant Honavar: Neural Network Design and the Complexity of Learning (Book Review). Machine Learning 9 : 95-98 (1992) Vasant Honavar, Leonard Uhr : Generation, Local Receptive Fields and Global Convergence Improve Perceptual Learning in Connectionist Networks. IJCAI 1989 : 180-185 1 [ 34 ] [ 63 ] [ 64 ] 2 [ 42 ] 3 [ 8 ] [ 36 ] 4 [ 20 ] 5 [ 51 ] [ 62 ] [ 63 ] [ 64 ] [ 65 ] 6 [ 70 ] 7 [ 36 ] 8 [ 36 ] 9 [ 36 ] 10 [ 48 ] 11 [ 51 ] 12 [ 66 ] 13 [ 23 ] [ 29 ] [ 30 ] [ 40 ] [ 41 ] [ 43 ] [ 45 ] [ 47 ] [ 49 ] [ 55 ] [ 56 ] [ 61 ] [ 62 ] [ 63 ] [ 64 ] [ 65 ] [ 66 ] 14 [ 37 ] 15 [ 4 ] 16 [ 37 ] 17 [ 37 ] 18 [ 21 ] 19 [ 29 ] [ 45 ] 20 [ 20 ] 21 [ 36 ] 22 [ 17 ] [ 34 ] [ 35 ] [ 39 ] [ 46 ] [ 48 ] [ 50 ] [ 63 ] [ 64 ] 23 [ 37 ] 24 [ 20 ] 25 [ 59 ] 26 [ 20 ] 27 [ 48 ] 28 [ 19 ] [ 27 ] [ 31 ] [ 32 ] [ 38 ] 29 [ 25 ] 30 [ 48 ] 31 [ 48 ] 32 [ 20 ] 33 [ 48 ] 34 [ 71 ] 35 [ 36 ] 36 [ 54 ] 37 [ 53 ] [ 58 ] [ 59 ] [ 67 ] [ 68 ] [ 69 ] 38 [ 37 ] 39 [ 48 ] 40 [ 56 ] 41 [ 36 ] 42 [ 42 ] 43 [ 37 ] 44 [ 31 ] [ 70 ] 45 [ 36 ] 46 [ 71 ] 47 [ 9 ] [ 10 ] [ 12 ] [ 26 ] 48 [ 36 ] 49 [ 19 ] [ 27 ] [ 31 ] [ 32 ] [ 38 ] 50 [ 27 ] 51 [ 14 ] 52 [ 5 ] [ 6 ] [ 7 ] [ 11 ] [ 14 ] [ 16 ] [ 17 ] [ 18 ] [ 22 ] [ 24 ] 53 [ 41 ] [ 49 ] [ 55 ] [ 56 ] [ 62 ] [ 63 ] [ 64 ] [ 65 ] [ 70 ] [ 71 ] 54 [ 27 ] 55 [ 36 ] 56 [ 28 ] 57 [ 36 ] 58 [ 41 ] [ 43 ] 59 [ 37 ] 60 [ 36 ] 61 [ 36 ] 62 [ 35 ] [ 39 ] 63 [ 36 ] 64 [ 48 ] 65 [ 37 ] 66 [ 23 ] [ 30 ] [ 33 ] [ 40 ] [ 41 ] [ 43 ] [ 47 ] [ 53 ] [ 58 ] [ 60 ] [ 63 ] [ 64 ] [ 67 ] [ 68 ] [ 69 ] 67 [ 31 ] 68 [ 15 ] 69 [ 20 ] 70 [ 51 ] 71 [ 1 ] [ 3 ] 72 [ 28 ] 73 [ 28 ] 74 [ 68 ] 75 [ 37 ] 76 [ 48 ] 77 [ 37 ] 78 [ 35 ] [ 39 ] 79 [ 38 ] 80 [ 36 ] 81 [ 9 ] [ 10 ] [ 19 ] [ 26 ] [ 27 ] [ 31 ] [ 32 ] [ 38 ] 82 [ 12 ] 83 [ 57 ] 84 [ 60 ] 85 [ 46 ] [ 48 ] [ 50 ] 86 [ 6 ] [ 13 ] [ 16 ] [ 17 ] [ 54 ] 87 [ 37 ] 88 [ 65 ] 89 [ 33 ] [ 44 ] [ 52 ] [ 53 ] [ 54 ] [ 57 ] [ 58 ] [ 61 ] [ 62 ] [ 67 ]  ©2006 Association for Computing Machinery |
