Generation, Local Receptive Fields and Global Convergence Improve Perceptual Learning in Connectionist Networks. - Vasant G. Honavar; Leonard Uhr (IJCAI, 1989)

Coordination and control structures and processes: possibilities for connectionist networks (CN). - Vasant G. Honavar; Leonard Uhr (J. Exp. Theor. Artif. Intell., 1990)

Neural Network Design and the Complexity of Learning (Book Review). - Vasant G. Honavar (Mach. Learn., 1992)

Generative learning structures and processes for generalized connectionist networks. - Vasant G. Honavar; Leonard Uhr (Inf. Sci., 1993)

A Neural Architecture for Content as well as Address-based Storage and Recall: Theory and Applications. - Chun-Hsien Chen; Vasant G. Honavar (Connect. Sci., 1995)

Experiments in Evolutionary Synthesis of Robotic Neurocontrollers. - Karthik Balakrishnan; Vasant G. Honavar (AAAI/IAAI, Vol. 2, 1996)

Analysis of Utility-Theoretic Heuristics for Intelligent Adaptive Network Routing. - Armin R. Mikler; Vasant G. Honavar; Johnny S. Wong (AAAI/IAAI, Vol. 1, 1996)

An Incremental Interactive Algorithm for Regular Grammar Inference. - Rajesh Parekh; Vasant G. Honavar (AAAI/IAAI, Vol. 2, 1996)

Constructive Neural Network Learning Algorithms. - Rajesh Parekh; Jihoon Yang; Vasant G. Honavar (AAAI/IAAI, Vol. 2, 1996)

An incremental interactive algorithm for grammar inference. - Rajesh Parekh; Vasant G. Honavar (ICGI, 1996)

MUpstart-a constructive neural network learning algorithm for multi-category pattern classification. - Rajesh Parekh; Jihoon Yang; Vasant G. Honavar (ICNN, 1997)

Pruning strategies for the MTiling constructive learning algorithm. - Rajesh Parekh; Jihoon Yang; Vasant G. Honavar (ICNN, 1997)

Quo Vadis - A Framework for Intelligent Routing in Large Communication Networks. - Armin R. Mikler; Johnny S. Wong; Vasant G. Honavar (J. Syst. Softw., 1997)

A Polynominal Time Incremental Algorithm for Learning DFA. - Rajesh Parekh; Codrin M. Nichitiu; Vasant G. Honavar (ICGI, 1998)

Feature Subset Selection Using a Genetic Algorithm. - Jihoon Yang; Vasant G. Honavar (IEEE Intell. Syst., 1998)

An object oriented approach to simulating large communication networks. - Armin R. Mikler; Johnny S. K. Wong; Vasant G. Honavar (J. Syst. Softw., 1998)

Feature Selection Using a Genetic Algorithm for Intrusion Detection. - Guy G. Helmer; Johnny S. Wong; Vasant G. Honavar; Les Miller (GECCO, 1999)

Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples. - Rajesh Parekh; Vasant G. Honavar (ICML, 1999)

Data-Driven Theory Refinement Using KBDistAl. - Jihoon Yang; Rajesh Parekh; Vasant G. Honavar; Drena Dobbs (IDA, 1999)

Data-driven theory refinement algorithms for bioinformatics. - Jihoon Yang; Rajesh Parekh; Vasant G. Honavar; Drena Dobbs (IJCNN, 1999)

Spatial Learning and Localization in Rodents: A Computational Model of the Hippocampus and its Implications for Mobile Robots. - Karthik Balakrishnan; Olivier Bousquet; Vasant G. Honavar (Adapt. Behav., 1999)

Integration of cognitive systems across disciplinary boundaries. - Ron Sun; Vasant G. Honavar; Gregg C. Oden (Cogn. Syst. Res., 1999)

DistAl: An inter-pattern distance-based constructive learning algorithm. - Jihoon Yang; Rajesh Parekh; Vasant G. Honavar (Intell. Data Anal., 1999)

A neural-network architecture for syntax analysis. - Chun-Hsien Chen; Vasant G. Honavar (IEEE Trans. Neural Networks, 1999)

Incremental and Distributed Learning with Support Vector Machines. - Doina Caragea; Adrian Silvescu; Vasant G. Honavar (AAAI/IAAI, 2000)

LEARN++: an incremental learning algorithm for multilayer perceptron networks. - Robi Polikar; Lalita Udpa; Satish S. Udpa; Vasant G. Honavar (ICASSP, 2000)

On the Relationship between Models for Learning in Helpful Environments. - Rajesh Parekh; Vasant G. Honavar (ICGI, 2000)

Supporting organizational knowledge management with agents. - Prashant Pai; Leslie L. Miller; Vasant G. Honavar; Johnny Wong 001; Sree Nilakanta (IRMA Conference, 2000)

A Negotiation Model in Agent-mediated Electronic Commerce. - Mokdong Chug; Vasant G. Honavar (ISMSE, 2000)

An empirical comparison of the performance so single-layer algorithms for training threshold logic units. - Rajesh Parekh; Jihoon Yang; Vasant G. Honavar (Neural Parallel Sci. Comput., 2000)

Constructive neural-network learning algorithms for pattern classification. - Rajesh Parekh; Jihoon Yang; Vasant G. Honavar (IEEE Trans. Neural Networks Learn. Syst., 2000)

Detection and identification of odorants using an electronic nose. - Robi Polikar; Ruth Shinar; Vasant G. Honavar; Lalita Udpa; Marc D. Porter (ICASSP, 2001)

Gaining insights into support vector machine pattern classifiers using projection-based tour methods. - Doina Caragea; Dianne Cook; Vasant G. Honavar (KDD, 2001)

Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources. - Doina Caragea; Adrian Silvescu; Vasant G. Honavar (Emergent Neural Computational Architectures Based on Neuroscience, 2001)

Temporal Boolean Network Models of Genetic Networks and their Inference from Gene Expression Time Series. - Adrian Silvescu; Vasant G. Honavar (Complex Syst., 2001)

Autonomous agents for coordinated distributed parameterized heuristic routing in large dynamic communication networks. - Armin R. Mikler; Vasant G. Honavar; Johnny S. Wong (J. Syst. Softw., 2001)

SMART mobile agent facility. - Johnny Wong 001; Guy G. Helmer; Venkatraman Naganathan; Sriniwas Polavarapu; Vasant G. Honavar; Les Miller (J. Syst. Softw., 2001)

Introduction. - Vasant G. Honavar; Colin de la Higuera (Mach. Learn., 2001)

Learning DFA from Simple Examples. - Rajesh Parekh; Vasant G. Honavar (Mach. Learn., 2001)

Learn++: an incremental learning algorithm for supervised neural networks. - Robi Polikar; L. Upda; S. S. Upda; Vasant G. Honavar (IEEE Trans. Syst. Man Cybern. Part C, 2001)

Discovering Protein Function Classification Rules from Reduced Alphabet Representations of Protein Sequences. - Carson M. Andorf; Drena Dobbs; Vasant G. Honavar (JCIS, 2002)

Data-Driven Discovery of Protein Function Classifiers: Decision Trees Based on MEME Motifs outperform PROSITE Patterns and Profiles on Peptidase Families. - Xiangyun Wang; Diane Schroeder; Drena Dobbs; Vasant G. Honavar (JCIS, 2002)

Ontology-Driven Induction of Decision Trees at Multiple Levels of Abstraction. - Jun Zhang 002; Adrian Silvescu; Vasant G. Honavar (SARA, 2002)

Automated discovery of concise predictive rules for intrusion detection. - Guy G. Helmer; Johnny S. Wong; Vasant G. Honavar; Les Miller (J. Syst. Softw., 2002)

A Software Fault Tree Approach to Requirements Analysis of an Intrusion Detection System. - Guy G. Helmer; Johnny S. Wong; Mark Slagell; Vasant G. Honavar; Les Miller; Robyn R. Lutz (Requir. Eng., 2002)

Towards Simple, Easy-to-Understand, yet Accurate Classifiers. - Doina Caragea; Dianne Cook; Vasant G. Honavar (ICDM, 2003)

Learning from Attribute Value Taxonomies and Partially Specified Instances. - Jun Zhang 002; Vasant G. Honavar (ICML, 2003)

Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources. - Doina Caragea; Jaime Reinoso; Adrian Silvescu; Vasant G. Honavar (IIWeb, 2003)

A Multi-relational Decision Tree Learning Algorithm - Implementation and Experiments. - Anna Atramentov; Hector Leiva; Vasant G. Honavar (ILP, 2003)

Information Extraction and Integration from Heterogeneous, Distributed, Autonomous Information Sources : A Federated Ontology-Driven Query-Centric Approach. - Jaime Reinoso; Adrian Silvescu; Doina Caragea; Jyotishman Pathak; Vasant G. Honavar (IRI, 2003)

Learning Decision Trees form Distributed Heterogeneous Autonomous Data. - Doina Caragea; Adrian Silvescu; Vasant G. Honavar (MAICS, 2003)

Automated data-driven discovery of motif-based protein function classifiers. - Xiangyun Wang; Diane Schroeder; Drena Dobbs; Vasant G. Honavar (Inf. Sci., 2003)

Lightweight agents for intrusion detection. - Guy G. Helmer; Johnny S. Wong; Vasant G. Honavar; Les Miller; Yanxin Wang (J. Syst. Softw., 2003)

Learning Classifiers from Semantically Heterogeneous Data. - Doina Caragea; Jyotishman Pathak; Vasant G. Honavar (CoopIS/DOA/ODBASE (2), 2004)

Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data. - Jinu Joo; Jun Zhang 002; Jihoon Yang; Vasant G. Honavar (Discovery Science, 2004)

Collaborative Ontology Building with Wiki@nt - A Multi-agent Based Ontology Building Environment. - Jie Bao 001; Vasant G. Honavar (EON, 2004)

Generation of Attribute Value Taxonomies from Data for Data-Driven Construction of Accurate and Compact Classifiers. - Dae-Ki Kang; Adrian Silvescu; Jun Zhang 002; Vasant G. Honavar (ICDM, 2004)

AVT-NBL: An Algorithm for Learning Compact and Accurate Naïve Bayes Classifiers from Attribute Value Taxonomies and Data. - Jun Zhang 002; Vasant G. Honavar (ICDM, 2004)

Integration of Domain-Specific and Domain-Independent Ontologies for Colonoscopy Video Database Annotation. - Jie Bao 001; Yu Cao 002; Wallapak Tavanapong; Vasant G. Honavar (IKE, 2004)

A two-stage classifier for identification of protein-protein interface residues. - Changhui Yan; Drena Dobbs; Vasant G. Honavar (ISMB/ECCB (Supplement of Bioinformatics), 2004)

Ontology-Extended Component-Based Workflows : A Framework for Constructing Complex Workflows from Semantically Heterogeneous Software Components. - Jyotishman Pathak; Doina Caragea; Vasant G. Honavar (SWDB, 2004)

Predicting binding sites of hydrolase-inhibitor complexes by combining several methods. - Taner Z. Sen; Andrzej Kloczkowski; Robert L. Jernigan; Changhui Yan; Vasant G. Honavar; Kai-Ming Ho; Cai-Zhuang Wang; Yungok Ihm; Haibo Cao; Xun Gu; Drena Dobbs (BMC Bioinform., 2004)

A Framework for Learning from Distributed Data Using Sufficient Statistics and Its Application to Learning Decision Trees. - Doina Caragea; Adrian Silvescu; Vasant G. Honavar (Int. J. Hybrid Intell. Syst., 2004)

Identification of interface residues in protease-inhibitor and antigen-antibody complexes: a support vector machine approach. - Changhui Yan; Vasant G. Honavar; Drena Dobbs (Neural Comput. Appl., 2004)

Learning Support Vector Machines from Distributed Data Sources. - Cornelia Caragea; Doina Caragea; Vasant G. Honavar (AAAI, 2005)

Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. - Doina Caragea; Jun Zhang 002; Jie Bao 001; Jyotishman Pathak; Vasant G. Honavar (ALT, 2005)

Information Integration from Semantically Heterogeneous Biological Data Sources. - Doina Caragea; Jie Bao 001; Jyotishman Pathak; Adrian Silvescu; Carson M. Andorf; Drena Dobbs; Vasant G. Honavar (DEXA Workshops, 2005)

Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources. - Doina Caragea; Jyotishman Pathak; Jie Bao 001; Adrian Silvescu; Carson M. Andorf; Drena Dobbs; Vasant G. Honavar (DILS, 2005)

Learning Ontology-Aware Classifiers. - Jun Zhang 002; Doina Caragea; Vasant G. Honavar (Discovery Science, 2005)

Discriminatively Trained Markov Model for Sequence Classification. - Oksana Yakhnenko; Adrian Silvescu; Vasant G. Honavar (ICDM, 2005)

Learning Classifiers for Misuse Detection Using a Bag of System Calls Representation. - Dae-Ki Kang; Doug Fuller; Vasant G. Honavar (ISI, 2005)

Multinomial Event Model Based Abstraction for Sequence and Text Classification. - Dae-Ki Kang; Jun Zhang 002; Adrian Silvescu; Vasant G. Honavar (SARA, 2005)

Learning Classifiers Using Hierarchically Structured Class Taxonomies. - Feihong Wu; Jun Zhang 002; Vasant G. Honavar (SARA, 2005)

A framework for semantic web services discovery. - Jyotishman Pathak; Neeraj Koul; Doina Caragea; Vasant G. Honavar (WIDM, 2005)

Identifying Interaction Sites in "Recalcitrant" Proteins: Predicted Protein and Rna Binding Sites in Rev Proteins of Hiv-1 and Eiav Agree with Experimental Data - Michael Terribilini; Jae-Hyung Lee; Changhui Yan; Robert L. Jernigan; Susan Carpenter; Vasant G. Honavar; Drena Dobbs (CoRR, 2005)

Representing and Reasoning with Modular Ontologies. - Jie Bao 001; Vasant G. Honavar (AAAI Fall Symposium: Semantic Web for Collaborative Knowledge Acquisition, 2006)

A General Strategy for Knowledge Acquisition from Semantically Heterogeneous Data Sources. - Doina Caragea; Jie Bao 001; Vasant G. Honavar (AAAI Fall Symposium: Semantic Web for Collaborative Knowledge Acquisition, 2006)

Experimental Comparison of Feature Subset Selection Using GA and ACO Algorithm. - Keunjoon Lee; Jinu Joo; Jihoon Yang; Vasant G. Honavar (ADMA, 2006)

Modular Ontologies - A Formal Investigation of Semantics and Expressivity. - Jie Bao 001; Doina Caragea; Vasant G. Honavar (ASWC, 2006)

Towards Collaborative Environments for Ontology Construction and Sharing. - Jie Bao 001; Doina Caragea; Vasant G. Honavar (CTS, 2006)

Learning Classifiers from Distributed, Ontology-Extended Data Sources. - Doina Caragea; Jun Zhang 002; Jyotishman Pathak; Vasant G. Honavar (DaWaK, 2006)

A Tool for Collaborative Construction of Large Biological Ontologies. - Jie Bao 001; Zhiliang Hu; Doina Caragea; James M. Reecy; Vasant G. Honavar (DEXA Workshops, 2006)

Parallel Web Service Composition in MoSCoE: A Choreography-Based Approach. - Jyotishman Pathak; Samik Basu 001; Robyn R. Lutz; Vasant G. Honavar (ECOWS, 2006)

Condition Data Aggregation with Application to Failure Rate Calculation of Power Transformers. - Jyotishman Pathak; Yong Jiang; Vasant G. Honavar; James D. McCalley (HICSS, 2006)

Auto-steered Information-Decision Processes for Electric System Asset Management. - James D. McCalley; Vasant G. Honavar; Sarah M. Ryan; William Q. Meeker; Ronald A. Roberts; Daji Qiao; Yuan Li (International Conference on Computational Science (3), 2006)

MoSCoE: A Framework for Modeling Web Service Composition and Execution. - Jyotishman Pathak; Samik Basu 001; Robyn R. Lutz; Vasant G. Honavar (ICDE Workshops, 2006)

Modeling Web Services by Iterative Reformulation of Functional and Non-functional Requirements. - Jyotishman Pathak; Samik Basu 001; Vasant G. Honavar (ICSOC, 2006)

A Service-Oriented Architecture for Electric Power Transmission System Asset Management. - Jyotishman Pathak; Yuan Li; Vasant G. Honavar; James D. McCalley (ICSOC Workshops, 2006)

Selecting and Composing Web Services through Iterative Reformulation of Functional Specifications. - Jyotishman Pathak; Samik Basu 001; Robyn R. Lutz; Vasant G. Honavar (ICTAI, 2006)

Independence, Decomposability and Functions which Take Values into an Abelian Group. - Adrian Silvescu; Vasant G. Honavar (AI&M, 2006)

Adapt OWL as a Modular Ontology Language. - Jie Bao 001; Vasant G. Honavar (OWLED, 2006)

RNBL-MN: A Recursive Naive Bayes Learner for Sequence Classification. - Dae-Ki Kang; Adrian Silvescu; Vasant G. Honavar (PAKDD, 2006)

TRIPPER: Rule Learning Using Taxonomies. - Flavian Vasile; Adrian Silvescu; Dae-Ki Kang; Vasant G. Honavar (PAKDD, 2006)

On the Semantics of Linking and Importing in Modular Ontologies. - Jie Bao 001; Doina Caragea; Vasant G. Honavar (ISWC, 2006)

Package-Based Description Logics - Preliminary Results. - Jie Bao 001; Doina Caragea; Vasant G. Honavar (ISWC, 2006)

Divide and Conquer Semantic Web with Modular Ontologies - A Brief Review of Modular Ontology Language Formalisms. - Jie Bao 001; Vasant G. Honavar (WoMO, 2006)

A Tableau-Based Federated Reasoning Algorithm for Modular Ontologies. - Jie Bao 001; Doina Caragea; Vasant G. Honavar (Web Intelligence, 2006)

Predicting DNA-binding sites of proteins from amino acid sequence. - Changhui Yan; Michael Terribilini; Feihong Wu; Robert L. Jernigan; Drena Dobbs; Vasant G. Honavar (BMC Bioinform., 2006)

Towards the automatic generation of mobile agents for distributed intrusion detection system. - Yanxin Wang; Smruti Ranjan Behera; Johnny Wong 001; Guy G. Helmer; Vasant G. Honavar; Les Miller; Robyn R. Lutz; Mark Slagell (J. Syst. Softw., 2006)

Learning accurate and concise naïve Bayes classifiers from attribute value taxonomies and data. - Jun Zhang 002; Dae-Ki Kang; Adrian Silvescu; Vasant G. Honavar (Knowl. Inf. Syst., 2006)

A Semantic Importing Approach to Knowledge Reuse from Multiple Ontologies. - Jie Bao 001; Giora Slutzki; Vasant G. Honavar (AAAI, 2007)

Assessing the Performance of Macromolecular Sequence Classifiers. - Cornelia Caragea; Jivko Sinapov; Vasant G. Honavar; Drena Dobbs (BIBE, 2007)

Analysis of Protein Protein Dimeric Interfaces. - Feihong Wu; Fadi Towfic; Drena Dobbs; Vasant G. Honavar (BIBM, 2007)

Integrated Decision Algorithms for Auto-steered Electric Transmission System Asset Management. - James D. McCalley; Vasant G. Honavar; Sarah M. Ryan; William Q. Meeker; Daji Qiao; Ronald A. Roberts; Yuan Li; Jyotishman Pathak; Mujing Ye; Yili Hong 001 (International Conference on Computational Science (1), 2007)

On Context-Specific Substitutability of Web Services. - Jyotishman Pathak; Samik Basu 001; Vasant G. Honavar (ICWS, 2007)

Privacy-Preserving Reasoning on the SemanticWeb. - Jie Bao 001; Giora Slutzki; Vasant G. Honavar (Web Intelligence, 2007)

Reports on the 2006 AAAI Fall Symposia. - Joshua Clifford Bongard; Derek P. Brock; Samuel G. Collins; Ramani Duraiswami; Tim Finin; Ian Harrison; Vasant G. Honavar; Gregory S. Hornby; Ari K. Jónsson; Mike Kassoff; David Kortenkamp; Sanjeev Kumar; et al. (AI Mag., 2007)

Exploring inconsistencies in genome-wide protein function annotations: a machine learning approach. - Carson M. Andorf; Drena Dobbs; Vasant G. Honavar (BMC Bioinform., 2007)

Glycosylation site prediction using ensembles of Support Vector Machine classifiers. - Cornelia Caragea; Jivko Sinapov; Adrian Silvescu; Drena Dobbs; Vasant G. Honavar (BMC Bioinform., 2007)

Software fault tree and coloured Petri net-based specification, design and implementation of agent-based intrusion detection systems. - Guy G. Helmer; Johnny Wong 001; Mark Slagell; Vasant G. Honavar; Les Miller; Yanxin Wang; Xia Wang; Natalia Stakhanova (Int. J. Inf. Comput. Secur., 2007)

RNABindR: a server for analyzing and predicting RNA-binding sites in proteins. - Michael Terribilini; Jeffry D. Sander; Jae-Hyung Lee; Peter Zaback; Robert L. Jernigan; Vasant G. Honavar; Drena Dobbs (Nucleic Acids Res., 2007)

Assembling Composite Web Services from Autonomous Components. - Jyotishman Pathak; Samik Basu 001; Vasant G. Honavar (Emerging Artificial Intelligence Applications in Computer Engineering, 2007)

Toward Semantics-Enabled Infrastructure for Knowledge Acquisition from Distributed Data. - Vasant G. Honavar; Doina Caragea (Next Generation of Data Mining, 2008)

Composing Web Services through Automatic Reformulation of Service Specifications. - Jyotishman Pathak; Samik Basu 001; Vasant G. Honavar (IEEE SCC (1), 2008)

On the Decidability of Role Mappings between Modular Ontologies. - Jie Bao 001; George Voutsadakis; Giora Slutzki; Vasant G. Honavar (AAAI, 2008)

Towards Semantics-Enabled Distributed Infrastructure for Knowledge Acquisition. - Vasant G. Honavar; Doina Caragea (AAAI Spring Symposium: Semantic Scientific Knowledge Integration, 2008)

Using Global Sequence Similarity to Enhance Biological Sequence Labeling. - Cornelia Caragea; Jivko Sinapov; Drena Dobbs; Vasant G. Honavar (BIBM, 2008)

Predicting Protective Linear B-Cell Epitopes Using Evolutionary Information. - Yasser El-Manzalawy; Drena Dobbs; Vasant G. Honavar (BIBM, 2008)

Complexes of on-line self assembly. - Neeraj Koul; Jim Lathrop; Jack H. Lutz; Vasant G. Honavar (EIT, 2008)

Unsupervised Learning of Probabilistic Context-Free Grammar using Iterative Biclustering. - Kewei Tu; Vasant G. Honavar (ICGI, 2008)

TCP-Compose* - A TCP-Net Based Algorithm for Efficient Composition of Web Services Using Qualitative Preferences. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (ICSOC, 2008)

Attribute Value Taxonomy Generation through Matrix Based Adaptive Genetic Algorithm. - Hyunsung Jo; Yong-chan Na; Byonghwa Oh; Jihoon Yang; Vasant G. Honavar (ICTAI (1), 2008)

Striking Similarities in Diverse Telomerase Proteins Revealed by Combining Structure Prediction and Machine Learning Approaches. - Jae-Hyung Lee; Michael Hamilton; Colin Gleeson; Cornelia Caragea; Peter Zaback; Jeffry D. Sander; Li C. Xue; Feihong Wu; Michael Terribilini; Vasant G. Honavar; Drena Dobbs (Pacific Symposium on Biocomputing, 2008)

On Utilizing Qualitative Preferences in Web Service Composition: A CP-net Based Approach. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (SERVICES I, 2008)

Learning Classifiers from Large Databases Using Statistical Queries. - Neeraj Koul; Cornelia Caragea; Vasant G. Honavar; Vikas Bahirwani; Doina Caragea (Web Intelligence, 2008)

Federated ALCI: Preliminary Report. - George Voutsadakis; Giora Slutzki; Vasant G. Honavar; Jie Bao 001 (Web Intelligence, 2008)

Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable. - Myron Peto; Andrzej Kloczkowski; Vasant G. Honavar; Robert L. Jernigan (BMC Bioinform., 2008)

MOSCOE: an Approach for Composing Web Services through Iterative Reformulation of Functional Specifications. - Jyotishman Pathak; Samik Basu 001; Robyn R. Lutz; Vasant G. Honavar (Int. J. Artif. Intell. Tools, 2008)

Visual Methods for Examining SVM Classifiers. - Doina Caragea; Dianne Cook; Hadley Wickham; Vasant G. Honavar (Visual Data Mining, 2008)

Web Service Substitution Based on Preferences Over Non-functional Attributes. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (IEEE SCC, 2009)

Detection of Gene Orthology Based on Protein-Protein Interaction Networks. - Fadi Towfic; M. Heather West Greenlee; Vasant G. Honavar (BIBM, 2009)

Multiple label prediction for image annotation with multiple Kernel correlation models. - Oksana Yakhnenko; Vasant G. Honavar (CVPR Workshops, 2009)

MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio. - Yasser El-Manzalawy; Vasant G. Honavar (Discovery Science, 2009)

Combining Super-Structuring and Abstraction on Sequence Classification. - Adrian Silvescu; Cornelia Caragea; Vasant G. Honavar (ICDM, 2009)

Learning Link-Based Classifiers from Ontology-Extended Textual Data. - Cornelia Caragea; Doina Caragea; Vasant G. Honavar (ICTAI, 2009)

Design and Implementation of a Query Planner for Data Integration. - Neeraj Koul; Vasant G. Honavar (ICTAI, 2009)

Learning Link-Based Naïve Bayes Classifiers from Ontology-Extended Distributed Data. - Cornelia Caragea; Doina Caragea; Vasant G. Honavar (OTM Conferences (2), 2009)

Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence. - Oksana Yakhnenko; Vasant G. Honavar (SDM, 2009)

Aligning Biomolecular Networks Using Modular Graph Kernels. - Fadi Towfic; M. Heather West Greenlee; Vasant G. Honavar (WABI, 2009)

Mixture of experts models to exploit global sequence similarity on biomolecular sequence labeling. - Cornelia Caragea; Jivko Sinapov; Drena Dobbs; Vasant G. Honavar (BMC Bioinform., 2009)

Efficient Markov Network Structure Discovery Using Independence Tests. - Facundo Bromberg; Dimitris Margaritis 001; Vasant G. Honavar (J. Artif. Intell. Res., 2009)

Knowledge Acquisition from Semantically Heterogeneous Data. - Doina Caragea; Vasant G. Honavar (Encyclopedia of Data Warehousing and Mining, 2009)

Machine Learning in Computational Biology. - Cornelia Caragea; Vasant G. Honavar (Encyclopedia of Database Systems, 2009)

Package-Based Description Logics. - Jie Bao 001; George Voutsadakis; Giora Slutzki; Vasant G. Honavar (Modular Ontologies, 2009)

Dominance Testing via Model Checking. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (AAAI, 2010)

Semi-supervised sequence classification using abstraction augmented Markov models. - Cornelia Caragea; Adrian Silvescu; Doina Caragea; Vasant G. Honavar (BCB, 2010)

A framework for developing epitope prediction tools. - Yasser El-Manzalawy; Vasant G. Honavar (BCB, 2010)

Scalable, updatable predictive models for sequence data. - Neeraj Koul; Ngot Bui; Vasant G. Honavar (BIBM, 2010)

Abstraction Augmented Markov Models. - Cornelia Caragea; Adrian Silvescu; Doina Caragea; Vasant G. Honavar (ICDM, 2010)

Ontology-guided Extraction of Complex Nested Relationships. - Sushain Pandit; Vasant G. Honavar (ICTAI (2), 2010)

Automata-Based Verification of Security Requirements of Composite Web Services. - Hongyu Sun 001; Samik Basu 001; Vasant G. Honavar; Robyn R. Lutz (ISSRE, 2010)

Efficient Dominance Testing for Unconditional Preferences. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (KR, 2010)

Identifying and Eliminating Inconsistencies in Mappings across Hierarchical Ontologies. - Bhavesh Sanghvi; Neeraj Koul; Vasant G. Honavar (OTM Conferences (2), 2010)

Secrecy-Preserving Query Answering for Instance Checking in EL mathcal{EL}. - Jia Tao 001; Giora Slutzki; Vasant G. Honavar (RR, 2010)

Learning in Presence of Ontology Mapping Errors. - Neeraj Koul; Vasant G. Honavar (Web Intelligence, 2010)

Failure Analysis for Composition of Web Services Represented as Labeled Transition Systems. - Dinanath Nadkarni; Samik Basu 001; Vasant G. Honavar; Robyn R. Lutz (WS-FM, 2010)

Semi-supervised prediction of protein subcellular localization using abstraction augmented Markov models. - Cornelia Caragea; Doina Caragea; Adrian Silvescu; Vasant G. Honavar (BMC Bioinform., 2010)

Detection of gene orthology from gene co-expression and protein interaction networks. - Fadi Towfic; Susan VanderPlas; Casey A. Oliver; Oliver Couture; Christopher K. Tuggle; M. Heather West Greenlee; Vasant G. Honavar (BMC Bioinform., 2010)

Struct-NB: predicting protein-RNA binding sites using structural features. - Fadi Towfic; Cornelia Caragea; David C. Gemperline; Drena Dobbs; Vasant G. Honavar (Int. J. Data Min. Bioinform., 2010)

Verifying Intervention Policies to Counter Infection Propagation over Networks: A Model Checking Approach. - Ganesh Ram Santhanam; Yuly Suvorov; Samik Basu 001; Vasant G. Honavar (AAAI, 2011)

Identifying Sustainable Designs Using Preferences over Sustainability Attributes. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (AAAI Spring Symposium: Artificial Intelligence and Sustainable Design, 2011)

Ranking docked models of protein-protein complexes using predicted partner-specific protein-protein interfaces: a preliminary study. - Li C. Xue; Rafael A. Jordan; Yasser El-Manzalawy; Drena Dobbs; Vasant G. Honavar (BCB, 2011)

Improving protein-RNA interface prediction by combining sequence homology based method with a naive Bayes classifier: preliminary results. - Li C. Xue; Rasna R. Walia; Yasser El-Manzalawy; Drena Dobbs; Vasant G. Honavar (BCB, 2011)

Abstraction Super-Structuring Normal Forms: Towards a Theory of Structural Induction. - Adrian Silvescu; Vasant G. Honavar (Algorithmic Probability and Friends, 2011)

Multi-Instance Multi-Label Learning for Image Classification with Large Vocabularies. - Oksana Yakhnenko; Vasant G. Honavar (BMVC, 2011)

On the Utility of Curricula in Unsupervised Learning of Probabilistic Grammars. - Kewei Tu; Vasant G. Honavar (IJCAI, 2011)

Exemplar-based Robust Coherent Biclustering. - Kewei Tu; Xixiu Ouyang; Dingyi Han; Vasant G. Honavar (SDM, 2011)

Learning Relational Bayesian Classifiers from RDF Data. - Harris T. Lin; Neeraj Koul; Vasant G. Honavar (ISWC (1), 2011)

Predicting RNA-Protein Interactions Using Only Sequence Information. - Usha Muppirala; Vasant G. Honavar; Drena Dobbs (BMC Bioinform., 2011)

HomPPI: A Class of Sequence Homology Based Protein-Protein Interface Prediction Methods. - Li C. Xue; Drena Dobbs; Vasant G. Honavar (BMC Bioinform., 2011)

Representing and Reasoning with Qualitative Preferences for Compositional Systems. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (J. Artif. Intell. Res., 2011)

PRIDB: a protein-RNA interface database. - Benjamin A. Lewis; Rasna R. Walia; Michael Terribilini; Jeff Ferguson; Charles Zheng 001; Vasant G. Honavar; Drena Dobbs (Nucleic Acids Res., 2011)

Predicting MHC-II Binding Affinity Using Multiple Instance Regression. - Yasser El-Manzalawy; Drena Dobbs; Vasant G. Honavar (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

Predicting protective bacterial antigens using random forest classifiers. - Yasser El-Manzalawy; Drena Dobbs; Vasant G. Honavar (BCB, 2012)

Learning predictive models from large distributed autonomous data sources. - Vasant G. Honavar (CIDU, 2012)

Unambiguity Regularization for Unsupervised Learning of Probabilistic Grammars. - Kewei Tu; Vasant G. Honavar (EMNLP-CoNLL, 2012)

Model Checking of Qualitative Sensitivity Preferences to Minimize Credential Disclosure. - Zachary J. Oster; Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (FACS, 2012)

Predicting protein-protein interface residues using local surface structural similarity. - Rafael A. Jordan; Yasser El-Manzalawy; Drena Dobbs; Vasant G. Honavar (BMC Bioinform., 2012)

Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. - Rasna R. Walia; Cornelia Caragea; Benjamin A. Lewis; Fadi Towfic; Michael Terribilini; Yasser El-Manzalawy; Drena Dobbs; Vasant G. Honavar (BMC Bioinform., 2012)

B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis. - Fadi Towfic; Shakti Gupta; Vasant G. Honavar; Shankar Subramaniam (Genom. Proteom. Bioinform., 2012)

PSPACE Tableau Algorithms for Acyclic Modalized $ boldsymbol{ mathcal{ALC}}$. - Jia Tao 001; Giora Slutzki; Vasant G. Honavar (J. Autom. Reason., 2012)

m-Transportability: Transportability of a Causal Effect from Multiple Environments. - Sanghack Lee; Vasant G. Honavar (AAAI, 2013)

Verifying Preferential Equivalence and Subsumption via Model Checking. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (ADT, 2013)

On the utility of abstraction in labeling actors in social networks. - Ngot Bui; Vasant G. Honavar (ASONAM, 2013)

Learning Classifiers from Chains of Multiple Interlinked RDF Data Stores. - Harris T. Lin; Vasant G. Honavar (BigData Congress, 2013)

Learning Classifiers from Distributional Data. - Harris T. Lin; Sanghack Lee; Ngot Bui; Vasant G. Honavar (BigData Congress, 2013)

Clustering remote RDF data using SPARQL update queries. - Letao Qi; Harris T. Lin; Vasant G. Honavar (ICDE Workshops, 2013)

Transportability from Multiple Environments with Limited Experiments. - Elias Bareinboim; Sanghack Lee; Vasant G. Honavar; Judea Pearl (NIPS, 2013)

Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability. - Sanghack Lee; Vasant G. Honavar (UAI, 2013)

Preference Based Service Adaptation Using Service Substitution. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (Web Intelligence, 2013)

An analysis of conformational changes upon RNA-protein binding. - Kannan Sankar; Rasna R. Walia; Carla M. Mann; Robert L. Jernigan; Vasant G. Honavar; Drena Dobbs (BCB, 2014)

Labeling Actors in Social Networks Using a Heterogeneous Graph Kernel. - Ngot Bui; Vasant G. Honavar (SBP, 2014)

A Conceptual Framework for Secrecy-preserving Reasoning in Knowledge Bases. - Jia Tao 001; Giora Slutzki; Vasant G. Honavar (ACM Trans. Comput. Log., 2014)

Learning classifiers from remote RDF data stores augmented with RDFS subclass hierarchies. - Harris T. Lin; Ngot Bui; Vasant G. Honavar (IEEE BigData, 2015)

Discovery Informatics in Biological and Biomedical Sciences: Research Challenges and Opportunities. - Vasant G. Honavar (Pacific Symposium on Biocomputing, 2015)

Temporal Causality of Social Support in an Online Community for Cancer Survivors. - Ngot Bui; John Yen; Vasant G. Honavar (SBP, 2015)

Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning. - Sanghack Lee; Vasant G. Honavar (ACI@UAI, 2015)

CRISNER: A Practically Efficient Reasoner for Qualitative Preferences. - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (CoRR, 2015)

On Learning Causal Models from Relational Data. - Sanghack Lee; Vasant G. Honavar (AAAI, 2016)

Labeling actors in multi-view social networks by integrating information from within and across multiple views. - Ngot Bui; Thanh Le; Vasant G. Honavar (IEEE BigData, 2016)

Session Introduction. - Drena Dobbs; Steven E. Brenner; Vasant G. Honavar; Robert L. Jernigan; Alain Laederach; Quaid Morris (PSB, 2016)

A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics. - Sanghack Lee; Vasant G. Honavar (UAI, 2016)

Accelerating Science: A Computing Research Agenda. - Vasant G. Honavar; Mark D. Hill; Katherine A. Yelick (CoRR, 2016)

Temporal Causality Analysis of Sentiment Change in a Cancer Survivor Network. - Ngot Bui; John Yen; Vasant G. Honavar (IEEE Trans. Comput. Soc. Syst., 2016)

Representing and Reasoning with Qualitative Preferences: Tools and Applications - Ganesh Ram Santhanam; Samik Basu 001; Vasant G. Honavar (Representing and Reasoning with Qualitative Preferences, 2016)

Sleep/wake state prediction and sleep parameter estimation using unsupervised classification via clustering. - Yasser El-Manzalawy; Orfeu M. Buxton; Vasant G. Honavar (BIBM, 2017)

Self-Discrepancy Conditional Independence Test. - Sanghack Lee; Vasant G. Honavar (UAI, 2017)

Towards Conditional Independence Test for Relational Data. - Sanghack Lee; Vasant G. Honavar (UAI, 2017)

Template-based protein-protein docking exploiting pairwise interfacial residue restraints. - Li C. Xue; João P. G. L. M. Rodrigues; Drena Dobbs; Vasant G. Honavar; Alexandre M. J. J. Bonvin (Briefings Bioinform., 2017)

Big Data, Data Science, and Civil Rights. - Solon Barocas; Elizabeth Bradley; Vasant G. Honavar; Foster J. Provost (CoRR, 2017)

Advances in Artificial Intelligence Require Progress Across all of Computer Science. - Gregory D. Hager; Randal E. Bryant; Eric Horvitz; Maja J. Mataric; Vasant G. Honavar (CoRR, 2017)

Advanced Cyberinfrastructure for Science, Engineering, and Public Policy. - Vasant G. Honavar; Katherine A. Yelick; Klara Nahrstedt; Holly E. Rushmeier; Jennifer Rexford; Mark D. Hill; Elizabeth Bradley; Elizabeth D. Mynatt (CoRR, 2017)

Microbiomarkers Discovery in Inflammatory Bowel Diseases using Network-Based Feature Selection. - Mostafa M. Abbas; Thanh Le; Halima Bensmail; Vasant G. Honavar; Yasser El-Manzalawy (BCB, 2018)

Toward personalized sleep-wake prediction from actigraphy. - Aria Khademi; Yasser El-Manzalawy; Orfeu M. Buxton; Vasant G. Honavar (BHI, 2018)

Top-N-Rank: A Scalable List-wise Ranking Method for Recommender Systems. - Junjie Liang; Jinlong Hu; Shoubin Dong; Vasant G. Honavar (IEEE BigData, 2018)

Multi-view Network Embedding via Graph Factorization Clustering and Co-regularized Multi-view Agreement. - Yiwei Sun; Ngot Bui; Tsung-Yu Hsieh; Vasant G. Honavar (ICDM Workshops, 2018)

Compositional Stochastic Average Gradient for Machine Learning and Related Applications. - Tsung-Yu Hsieh; Yasser El-Manzalawy; Yiwei Sun; Vasant G. Honavar (IDEAL (1), 2018)

PATENet: Pairwise Alignment of Time Evolving Networks. - Shlomit Gur; Vasant G. Honavar (MLDM (1), 2018)

A user similarity-based Top-N recommendation approach for mobile in-application advertising. - Jinlong Hu; Junjie Liang; Yuezhen Kuang; Vasant G. Honavar (Expert Syst. Appl., 2018)

Machine Learning in Computational Biology. - Cornelia Caragea; Vasant G. Honavar (Encyclopedia of Database Systems (2nd ed.), 2018)

Minimum Intervention Cover of a Causal Graph. - Saravanan Kandasamy 002; Arnab Bhattacharyya 001; Vasant G. Honavar (AAAI, 2019)

Adaptive Structural Co-regularization for Unsupervised Multi-view Feature Selection. - Tsung-Yu Hsieh; Yiwei Sun; Suhang Wang; Vasant G. Honavar (ICBK, 2019)

MEGAN: A Generative Adversarial Network for Multi-View Network Embedding. - Yiwei Sun; Suhang Wang; Tsung-Yu Hsieh; Xianfeng Tang; Vasant G. Honavar (IJCAI, 2019)

Towards Robust Relational Causal Discovery. - Sanghack Lee; Vasant G. Honavar (UAI, 2019)

Improving Image Captioning by Leveraging Knowledge Graphs. - Yimin Zhou 009; Yiwei Sun; Vasant G. Honavar (WACV, 2019)

Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. - Aria Khademi; Sanghack Lee; David Foley; Vasant G. Honavar (WWW, 2019)

Node Injection Attacks on Graphs via Reinforcement Learning. - Yiwei Sun; Suhang Wang; Xianfeng Tang; Tsung-Yu Hsieh; Vasant G. Honavar (CoRR, 2019)

The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario. - Thanh Le; Vasant G. Honavar (CoRR, 2019)

Algorithmic Bias in Recidivism Prediction: A Causal Perspective. - Aria Khademi; Vasant G. Honavar (CoRR, 2019)

Algorithmic Bias in Recidivism Prediction: A Causal Perspective (Student Abstract). - Aria Khademi; Vasant G. Honavar (AAAI, 2020)

LMLFM: Longitudinal Multi-Level Factorization Machine. - Junjie Liang; Dongkuan Xu; Yiwei Sun; Vasant G. Honavar (AAAI, 2020)

Dynamical Gaussian Process Latent Variable Model for Representation Learning from Longitudinal Data. - Thanh Le; Vasant G. Honavar (FODS, 2020)

Adversarial Attacks on Graph Neural Networks via Node Injections: A Hierarchical Reinforcement Learning Approach. - Yiwei Sun; Suhang Wang; Xianfeng Tang; Tsung-Yu Hsieh; Vasant G. Honavar (WWW, 2020)

iScore: a novel graph kernel-based function for scoring protein-protein docking models. - Cunliang Geng; Yong Jung; Nicolas Renaud; Vasant G. Honavar; Alexandre M. J. J. Bonvin; Li C. Xue (Bioinform., 2020)

A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution. - Aria Khademi; Vasant G. Honavar (CoRR, 2020)

Commuting Network Spillovers and COVID-19 Deaths Across US Counties. - Christopher Seto; Aria Khademi; Corina Graif; Vasant G. Honavar (CoRR, 2020)

Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time Intervals. - Tsung-Yu Hsieh; Suhang Wang; Yiwei Sun; Vasant G. Honavar (CoRR, 2020)

The Virtual Data Collaboratory: A Regional Cyberinfrastructure for Collaborative Data-Driven Research. - Manish Parashar; Anthony Simonet; Ivan Rodero; Forough Ghahramani; Grace Agnew; Ron Jantz; Vasant G. Honavar (Comput. Sci. Eng., 2020)

iScore: An MPI supported software for ranking protein-protein docking models based on a random walk graph kernel and support vector machines. - Nicolas Renaud; Yong Jung; Vasant G. Honavar; Cunliang Geng; Alexandre M. J. J. Bonvin; Li C. Xue (SoftwareX, 2020)

Longitudinal Deep Kernel Gaussian Process Regression. - Junjie Liang; Yanting Wu; Dongkuan Xu; Vasant G. Honavar (AAAI, 2021)

Shedding light into the darknet: scanning characterization and detection of temporal changes. - Rupesh Prajapati; Vasant G. Honavar; Dinghao Wu; John Yen; Michalis Kallitsis 001 (CoNEXT, 2021)

FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data. - Junjie Liang; Wenbo Guo 002; Tongbo Luo; Vasant G. Honavar; Gang Wang 011; Xinyu Xing 001 (NDSS, 2021)

Functional Autoencoders for Functional Data Representation Learning. - Tsung-Yu Hsieh; Yiwei Sun; Suhang Wang; Vasant G. Honavar (SDM, 2021)

Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns to Attend to Important Variables As Well As Time Intervals. - Tsung-Yu Hsieh; Suhang Wang; Yiwei Sun; Vasant G. Honavar (WSDM, 2021)

SrVARM: State Regularized Vector Autoregressive Model for Joint Learning of Hidden State Transitions and State-Dependent Inter-Variable Dependencies from Multi-variate Time Series. - Tsung-Yu Hsieh; Yiwei Sun; Xianfeng Tang; Suhang Wang; Vasant G. Honavar (WWW, 2021)

Zooming Into the Darknet: Characterizing Internet Background Radiation and its Structural Changes. - Michalis Kallitsis 001; Vasant G. Honavar; Rupesh Prajapati; Dinghao Wu; John Yen (CoRR, 2021)

Detecting and Interpreting Changes in Scanning Behavior in Large Network Telescopes. - Michael G. Kallitsis; Rupesh Prajapati; Vasant G. Honavar; Dinghao Wu; John Yen (IEEE Trans. Inf. Forensics Secur., 2022)

Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries. - Samik Basu 001; Vasant G. Honavar; Ganesh Ram Santhanam; Jia Tao 001 (ECAI, 2023)

A Simple, Fast Algorithm for Continual Learning from High-Dimensional Data. - Neil Ashtekar; Vasant G. Honavar (Tiny Papers @ ICLR, 2023)

License Forecasting and Scheduling for HPC. - Ahmed Burak Gulhan; Gulsum Gudukbay Akbulut; Amit Amritkar; Jack Sampson; Vasant G. Honavar; Adam Focht; Chuck Pavloski; Mahmut T. Kandemir (MASCOTS, 2023)

Forecasting User Interests Through Topic Tag Predictions in Online Health Communities. - Amogh Subbakrishna Adishesha; Lily Jakielaszek; Fariha Azhar; Peixuan Zhang; Vasant G. Honavar; Fenglong Ma; Chandra Belani; Prasenjit Mitra; Sharon Xiaolei Huang (IEEE J. Biomed. Health Informatics, 2023)

Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data. - Junjie Liang; Weijieying Ren; Hanifi Sahar; Vasant G. Honavar (AAAI, 2024)

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules. - Teng Xiao; Chao Cui; Huaisheng Zhu; Vasant G. Honavar (BIBM, 2024)

Causal Matching using Random Hyperplane Tessellations. - Abhishek Dalvi; Neil Ashtekar; Vasant G. Honavar (CLeaR, 2024)

How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective. - Teng Xiao; Mingxiao Li 004; Yige Yuan; Huaisheng Zhu; Chao Cui; Vasant G. Honavar (EMNLP, 2024)

TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules. - Weijieying Ren; Xiaoting Li 001; Huiyuan Chen; Vineeth Rakesh; Zhuoyi Wang; Mahashweta Das; Vasant G. Honavar (ICML, 2024)

Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. - Teng Xiao; Huaisheng Zhu; Zhiwei Zhang; Zhimeng Guo; Charu C. Aggarwal; Suhang Wang; Vasant G. Honavar (ICML, 2024)

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment. - Teng Xiao; Yige Yuan; Huaisheng Zhu; Mingxiao Li 004; Vasant G. Honavar (NeurIPS, 2024)

EsaCL: An Efficient Continual Learning Algorithm. - Weijieying Ren; Vasant G. Honavar (SDM, 2024)

EsaCL: Efficient Continual Learning of Sparse Models. - Weijieying Ren; Vasant G. Honavar (CoRR, 2024)

One-Shot Graph Representation Learning Using Hyperdimensional Computing. - Abhishek Dalvi; Vasant G. Honavar (CoRR, 2024)

3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs. - Huaisheng Zhu; Teng Xiao; Vasant G. Honavar (CoRR, 2024)

MolBind: Multimodal Alignment of Language, Molecules, and Proteins. - Teng Xiao; Chao Cui; Huaisheng Zhu; Vasant G. Honavar (CoRR, 2024)

Causal Effect Estimation Using Random Hyperplane Tessellations. - Abhishek Dalvi; Neil Ashtekar; Vasant G. Honavar (CoRR, 2024)

Regression with Large Language Models for Materials and Molecular Property Prediction. - Ryan Jacobs; Maciej P. Polak; Lane E. Schultz; Hamed Mahdavi; Vasant G. Honavar; Dane Morgan (CoRR, 2024)

Checking Consistency of CP-Theory Preferences in Polynomial Time. - Erik Rauer; Samik Basu 001; Vasant G. Honavar (AAAI, 2025)

DiaLLMs: EHR-Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. - Weijieying Ren; Tianxiang Zhao 001; Lei Wang 185; Tianchun Wang; Vasant G. Honavar (ACL (Findings), 2025)

SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. - Teng Xiao; Yige Yuan; Zhengyu Chen 001; Mingxiao Li 004; Shangsong Liang; Zhaochun Ren; Vasant G. Honavar (ICLR, 2025)

On a Connection Between Imitation Learning and RLHF. - Teng Xiao; Yige Yuan; Mingxiao Li 004; Zhengyu Chen 001; Vasant G. Honavar (ICLR, 2025)

DSPO: Direct Score Preference Optimization for Diffusion Model Alignment. - Huaisheng Zhu; Teng Xiao; Vasant G. Honavar (ICLR, 2025)

Hyperdimensional Representation Learning for Node Classification and Link Prediction. - Abhishek Dalvi; Vasant G. Honavar (WSDM, 2025)

Class Incremental Learning from First Principles: A Review. - Neil Ashtekar; Jingxi Zhu; Vasant G. Honavar (Trans. Mach. Learn. Res., 2025)

Deep Learning within Tabular Data: Foundations, Challenges, Advances and Future Directions. - Weijieying Ren; Tianxiang Zhao 001; Yuqing Huang; Vasant G. Honavar (CoRR, 2025)

C-HDNet: A Fast Hyperdimensional Computing Based Method for Causal Effect Estimation from Networked Observational Data. - Abhishek Dalvi; Neil Ashtekar; Vasant G. Honavar (CoRR, 2025)

A practical guide to machine learning interatomic potentials - Status and future. - Ryan Jacobs; Dane Morgan; Siamak Attarian; Jun Meng; Chen Shen; Zhenghao Wu; Clare Yijia Xie; Julia H. Yang; Nongnuch Artrith; Ben Blaiszik; Gerbrand Ceder; Kamal Choudhary; et al. (CoRR, 2025)

Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad Mathematics. - Hamed Mahdavi; Alireza Hashemi; Majid Daliri; Pegah Mohammadipour; Alireza Farhadi; Samira Malek; Yekta Yazdanifard; Amir Khasahmadi; Vasant G. Honavar (CoRR, 2025)

A Comprehensive Survey of Electronic Health Record Modeling: From Deep Learning Approaches to Large Language Models. - Weijieying Ren; Jingxi Zhu; Zehao Liu; Tianxiang Zhao 001; Vasant G. Honavar (CoRR, 2025)