| 2025 | AAAI | Checking Consistency of CP-Theory Preferences in Polynomial Time. | Erik Rauer, Samik Basu, Vasant G. Honavar |
| 2025 | ACL | DiaLLMs: EHR-Enhanced Clinical Conversational System for Clinical Test Recommendation and Diagnosis Prediction. | Weijieying Ren, Tianxiang Zhao, Lei Wang, Tianchun Wang, Vasant G. Honavar |
| 2025 | EMNLP | Reinforcement Learning for Large Language Models via Group Preference Reward Shaping. | Huaisheng Zhu, Siyuan Xu, Hangfan Zhang, Teng Xiao, Zhimeng Guo, Shijie Zhou, Shuyue Hu, Vasant G. Honavar |
| 2025 | ICLR | SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. | Teng Xiao, Yige Yuan, Zhengyu Chen, Mingxiao Li, Shangsong Liang, Zhaochun Ren, Vasant G. Honavar |
| 2025 | ICLR | On a Connection Between Imitation Learning and RLHF. | Teng Xiao, Yige Yuan, Mingxiao Li, Zhengyu Chen, Vasant G. Honavar |
| 2025 | ICLR | DSPO: Direct Score Preference Optimization for Diffusion Model Alignment. | Huaisheng Zhu, Teng Xiao, Vasant G. Honavar |
| 2025 | WSDM | Hyperdimensional Representation Learning for Node Classification and Link Prediction. | Abhishek Dalvi, Vasant G. Honavar |
| 2024 | AAAI | Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data. | Junjie Liang, Weijieying Ren, Hanifi Sahar, Vasant G. Honavar |
| 2024 | EMNLP | How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective. | Teng Xiao, Mingxiao Li, Yige Yuan, Huaisheng Zhu, Chao Cui, Vasant G. Honavar |
| 2024 | ICML | TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules. | Weijieying Ren, Xiaoting Li, Huiyuan Chen, Vineeth Rakesh, Zhuoyi Wang, Mahashweta Das, Vasant G. Honavar |
| 2024 | ICML | 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 |
| 2024 | SDM | EsaCL: An Efficient Continual Learning Algorithm. | Weijieying Ren, Vasant G. Honavar |
| 2023 | ECAI | Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries. | Samik Basu, Vasant G. Honavar, Ganesh Ram Santhanam, Jia Tao |
| 2023 | ICLR | A Simple, Fast Algorithm for Continual Learning from High-Dimensional Data. | Neil Ashtekar, Vasant G. Honavar |
| 2023 | MASCOTS | 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 |
| 2021 | AAAI | Longitudinal Deep Kernel Gaussian Process Regression. | Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant G. Honavar |
| 2021 | CoNEXT | Shedding light into the darknet: scanning characterization and detection of temporal changes. | Rupesh Prajapati, Vasant G. Honavar, Dinghao Wu, John Yen, Michalis Kallitsis |
| 2021 | NDSS | FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data. | Junjie Liang, Wenbo Guo, Tongbo Luo, Vasant G. Honavar, Gang Wang, Xinyu Xing |
| 2021 | WWW | 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 |
| 2021 | WSDM | 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 |
| 2021 | SDM | Functional Autoencoders for Functional Data Representation Learning. | Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, Vasant G. Honavar |
| 2020 | AAAI | Algorithmic Bias in Recidivism Prediction: A Causal Perspective (Student Abstract). | Aria Khademi, Vasant G. Honavar |
| 2020 | AAAI | LMLFM: Longitudinal Multi-Level Factorization Machine. | Junjie Liang, Dongkuan Xu, Yiwei Sun, Vasant G. Honavar |
| 2020 | WWW | 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 |
| 2019 | AAAI | Minimum Intervention Cover of a Causal Graph. | Saravanan Kandasamy, Arnab Bhattacharyya, Vasant G. Honavar |
| 2019 | IJCAI | MEGAN: A Generative Adversarial Network for Multi-View Network Embedding. | Yiwei Sun, Suhang Wang, Tsung-Yu Hsieh, Xianfeng Tang, Vasant G. Honavar |
| 2019 | WWW | Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. | Aria Khademi, Sanghack Lee, David Foley, Vasant G. Honavar |
| 2019 | WACV | Improving Image Captioning by Leveraging Knowledge Graphs. | Yimin Zhou, Yiwei Sun, Vasant G. Honavar |
| 2019 | UAI | Towards Robust Relational Causal Discovery. | Sanghack Lee, Vasant G. Honavar |
| 2018 | ICDM | Multi-view Network Embedding via Graph Factorization Clustering and Co-regularized Multi-view Agreement. | Yiwei Sun, Ngot Bui, Tsung-Yu Hsieh, Vasant G. Honavar |
| 2018 | IDEAL | Compositional Stochastic Average Gradient for Machine Learning and Related Applications. | Tsung-Yu Hsieh, Yasser El-Manzalawy, Yiwei Sun, Vasant G. Honavar |
| 2017 | UAI | Self-Discrepancy Conditional Independence Test. | Sanghack Lee, Vasant G. Honavar |
| 2017 | UAI | Towards Conditional Independence Test for Relational Data. | Sanghack Lee, Vasant G. Honavar |
| 2016 | AAAI | On Learning Causal Models from Relational Data. | Sanghack Lee, Vasant G. Honavar |
| 2016 | PSB | Session Introduction. | Drena Dobbs, Steven E. Brenner, Vasant G. Honavar, Robert L. Jernigan, Alain Laederach, Quaid Morris |
| 2016 | UAI | A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics. | Sanghack Lee, Vasant G. Honavar |
| 2015 | PSB | Discovery Informatics in Biological and Biomedical Sciences: Research Challenges and Opportunities. | Vasant G. Honavar |
| 2015 | UAI | Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning. | Sanghack Lee, Vasant G. Honavar |
| 2013 | AAAI | m-Transportability: Transportability of a Causal Effect from Multiple Environments. | Sanghack Lee, Vasant G. Honavar |
| 2013 | BigData | Learning Classifiers from Chains of Multiple Interlinked RDF Data Stores. | Harris T. Lin, Vasant G. Honavar |
| 2013 | BigData | Learning Classifiers from Distributional Data. | Harris T. Lin, Sanghack Lee, Ngot Bui, Vasant G. Honavar |
| 2013 | ICDE | Clustering remote RDF data using SPARQL update queries. | Letao Qi, Harris T. Lin, Vasant G. Honavar |
| 2013 | UAI | Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability. | Sanghack Lee, Vasant G. Honavar |
| 2012 | EMNLP | Unambiguity Regularization for Unsupervised Learning of Probabilistic Grammars. | Kewei Tu, Vasant G. Honavar |
| 2011 | AAAI | Verifying Intervention Policies to Counter Infection Propagation over Networks: A Model Checking Approach. | Ganesh Ram Santhanam, Yuly Suvorov, Samik Basu, Vasant G. Honavar |
| 2011 | BMVC | Multi-Instance Multi-Label Learning for Image Classification with Large Vocabularies. | Oksana Yakhnenko, Vasant G. Honavar |
| 2011 | IJCAI | On the Utility of Curricula in Unsupervised Learning of Probabilistic Grammars. | Kewei Tu, Vasant G. Honavar |
| 2011 | SDM | Exemplar-based Robust Coherent Biclustering. | Kewei Tu, Xixiu Ouyang, Dingyi Han, Vasant G. Honavar |
| 2010 | AAAI | Dominance Testing via Model Checking. | Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar |
| 2010 | ICDM | Abstraction Augmented Markov Models. | Cornelia Caragea, Adrian Silvescu, Doina Caragea, Vasant G. Honavar |
| 2010 | ICTAI | Ontology-guided Extraction of Complex Nested Relationships. | Sushain Pandit, Vasant G. Honavar |
| 2010 | ISSRE | Automata-Based Verification of Security Requirements of Composite Web Services. | Hongyu Sun, Samik Basu, Vasant G. Honavar, Robyn R. Lutz |
| 2010 | KR | Efficient Dominance Testing for Unconditional Preferences. | Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar |
| 2009 | CVPR | Multiple label prediction for image annotation with multiple Kernel correlation models. | Oksana Yakhnenko, Vasant G. Honavar |
| 2009 | DIS | MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio. | Yasser El-Manzalawy, Vasant G. Honavar |
| 2009 | ICDM | Combining Super-Structuring and Abstraction on Sequence Classification. | Adrian Silvescu, Cornelia Caragea, Vasant G. Honavar |
| 2009 | ICTAI | Learning Link-Based Classifiers from Ontology-Extended Textual Data. | Cornelia Caragea, Doina Caragea, Vasant G. Honavar |
| 2009 | ICTAI | Design and Implementation of a Query Planner for Data Integration. | Neeraj Koul, Vasant G. Honavar |
| 2009 | SDM | Multi-Modal Hierarchical Dirichlet Process Model for Predicting Image Annotation and Image-Object Label Correspondence. | Oksana Yakhnenko, Vasant G. Honavar |
| 2009 | WABI | Aligning Biomolecular Networks Using Modular Graph Kernels. | Fadi Towfic, M. Heather West Greenlee, Vasant G. Honavar |
| 2008 | AAAI | On the Decidability of Role Mappings between Modular Ontologies. | Jie Bao, George Voutsadakis, Giora Slutzki, Vasant G. Honavar |
| 2008 | ICSOC | TCP-Compose* - A TCP-Net Based Algorithm for Efficient Composition of Web Services Using Qualitative Preferences. | Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar |
| 2008 | ICTAI | Attribute Value Taxonomy Generation through Matrix Based Adaptive Genetic Algorithm. | Hyunsung Jo, Yong-chan Na, Byonghwa Oh, Jihoon Yang, Vasant G. Honavar |
| 2008 | PSB | 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 |
| 2008 | SERVICES | On Utilizing Qualitative Preferences in Web Service Composition: A CP-net Based Approach. | Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar |
| 2007 | AAAI | A Semantic Importing Approach to Knowledge Reuse from Multiple Ontologies. | Jie Bao, Giora Slutzki, Vasant G. Honavar |
| 2007 | BIBE | Assessing the Performance of Macromolecular Sequence Classifiers. | Cornelia Caragea, Jivko Sinapov, Vasant G. Honavar, Drena Dobbs |
| 2007 | ICCS | 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 |
| 2007 | ICWS | On Context-Specific Substitutability of Web Services. | Jyotishman Pathak, Samik Basu, Vasant G. Honavar |
| 2006 | ADMA | Experimental Comparison of Feature Subset Selection Using GA and ACO Algorithm. | Keunjoon Lee, Jinu Joo, Jihoon Yang, Vasant G. Honavar |
| 2006 | DaWaK | Learning Classifiers from Distributed, Ontology-Extended Data Sources. | Doina Caragea, Jun Zhang, Jyotishman Pathak, Vasant G. Honavar |
| 2006 | ICCS | 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 |
| 2006 | ICDE | MoSCoE: A Framework for Modeling Web Service Composition and Execution. | Jyotishman Pathak, Samik Basu, Robyn R. Lutz, Vasant G. Honavar |
| 2006 | ISAIM | Independence, Decomposability and Functions which Take Values into an Abelian Group. | Adrian Silvescu, Vasant G. Honavar |
| 2006 | ICSOC | Modeling Web Services by Iterative Reformulation of Functional and Non-functional Requirements. | Jyotishman Pathak, Samik Basu, Vasant G. Honavar |
| 2006 | ICSOC | A Service-Oriented Architecture for Electric Power Transmission System Asset Management. | Jyotishman Pathak, Yuan Li, Vasant G. Honavar, James D. McCalley |
| 2006 | ICTAI | Selecting and Composing Web Services through Iterative Reformulation of Functional Specifications. | Jyotishman Pathak, Samik Basu, Robyn R. Lutz, Vasant G. Honavar |
| 2006 | PAKDD | RNBL-MN: A Recursive Naive Bayes Learner for Sequence Classification. | Dae-Ki Kang, Adrian Silvescu, Vasant G. Honavar |
| 2006 | PAKDD | TRIPPER: Rule Learning Using Taxonomies. | Flavian Vasile, Adrian Silvescu, Dae-Ki Kang, Vasant G. Honavar |
| 2006 | SDM | Efficient Markov Network Structure Discovery using Independence Tests. | Facundo Bromberg, Dimitris Margaritis, Vasant G. Honavar |
| 2005 | AAAI | Learning Support Vector Machines from Distributed Data Sources. | Cornelia Caragea, Doina Caragea, Vasant G. Honavar |
| 2005 | ALT | Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. | Doina Caragea, Jun Zhang, Jie Bao, Jyotishman Pathak, Vasant G. Honavar |
| 2005 | DIS | Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources. | Doina Caragea, Jun Zhang, Jie Bao, Jyotishman Pathak, Vasant G. Honavar |
| 2005 | DIS | Learning Ontology-Aware Classifiers. | Jun Zhang, Doina Caragea, Vasant G. Honavar |
| 2005 | ICDM | Discriminatively Trained Markov Model for Sequence Classification. | Oksana Yakhnenko, Adrian Silvescu, Vasant G. Honavar |
| 2005 | ISI | Learning Classifiers for Misuse Detection Using a Bag of System Calls Representation. | Dae-Ki Kang, Doug Fuller, Vasant G. Honavar |
| 2004 | CoopIS | Learning Classifiers from Semantically Heterogeneous Data. | Doina Caragea, Jyotishman Pathak, Vasant G. Honavar |
| 2004 | DIS | Generating AVTs Using GA for Learning Decision Tree Classifiers with Missing Data. | Jinu Joo, Jun Zhang, Jihoon Yang, Vasant G. Honavar |
| 2004 | ICDM | Generation of Attribute Value Taxonomies from Data for Data-Driven Construction of Accurate and Compact Classifiers. | Dae-Ki Kang, Adrian Silvescu, Jun Zhang, Vasant G. Honavar |
| 2004 | ICDM | AVT-NBL: An Algorithm for Learning Compact and Accurate Nave Bayes Classifiers from Attribute Value Taxonomies and Data. | Jun Zhang, Vasant G. Honavar |
| 2004 | IKE | Integration of Domain-Specific and Domain-Independent Ontologies for Colonoscopy Video Database Annotation. | Jie Bao, Yu Cao, Wallapak Tavanapong, Vasant G. Honavar |
| 2004 | ISMB | A two-stage classifier for identification of protein-protein interface residues. | Changhui Yan, Drena Dobbs, Vasant G. Honavar |
| 2003 | ICDM | Towards Simple, Easy-to-Understand, yet Accurate Classifiers. | Doina Caragea, Dianne Cook, Vasant G. Honavar |
| 2003 | ICML | Learning from Attribute Value Taxonomies and Partially Specified Instances. | Jun Zhang, Vasant G. Honavar |
| 2003 | IJCAI | Statistics Gathering for Learning from Distributed, Heterogeneous and Autonomous Data Sources. | Doina Caragea, Jaime Reinoso, Adrian Silvescu, Vasant G. Honavar |
| 2003 | ILP | A Multi-relational Decision Tree Learning Algorithm - Implementation and Experiments. | Anna Atramentov, Hector Leiva, Vasant G. Honavar |
| 2003 | IRI | 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 |
| 2001 | ICASSP | Detection and identification of odorants using an electronic nose. | Robi Polikar, Ruth Shinar, Vasant G. Honavar, Lalita Udpa, Marc D. Porter |
| 2001 | KDD | Gaining insights into support vector machine pattern classifiers using projection-based tour methods. | Doina Caragea, Dianne Cook, Vasant G. Honavar |
| 2000 | AAAI | Incremental and Distributed Learning with Support Vector Machines. | Doina Caragea, Adrian Silvescu, Vasant G. Honavar |
| 2000 | ICASSP | LEARN++: an incremental learning algorithm for multilayer perceptron networks. | Robi Polikar, Lalita Udpa, Satish S. Udpa, Vasant G. Honavar |
| 1999 | GECCO | Feature Selection Using a Genetic Algorithm for Intrusion Detection. | Guy G. Helmer, Johnny S. Wong, Vasant G. Honavar, Les Miller |
| 1999 | ICML | Simple DFA are Polynomially Probably Exactly Learnable from Simple Examples. | Rajesh Parekh, Vasant G. Honavar |
| 1999 | IJCNN | Data-driven theory refinement algorithms for bioinformatics. | Jihoon Yang, Rajesh Parekh, Vasant G. Honavar, Drena Dobbs |
| 1999 | IDA | Data-Driven Theory Refinement Using | Jihoon Yang, Rajesh Parekh, Vasant G. Honavar, Drena Dobbs |
| 1997 | ALT | Learning DFA from Simple Examples. | Rajesh Parekh, Vasant G. Honavar |
| 1996 | AAAI | Experiments in Evolutionary Synthesis of Robotic Neurocontrollers. | Karthik Balakrishnan, Vasant G. Honavar |
| 1996 | AAAI | Analysis of Utility-Theoretic Heuristics for Intelligent Adaptive Network Routing. | Armin R. Mikler, Vasant G. Honavar, Johnny S. Wong |
| 1996 | AAAI | An Incremental Interactive Algorithm for Regular Grammar Inference. | Rajesh Parekh, Vasant G. Honavar |
| 1996 | AAAI | Constructive Neural Network Learning Algorithms. | Rajesh Parekh, Jihoon Yang, Vasant G. Honavar |
| 1989 | IJCAI | Generation, Local Receptive Fields and Global Convergence Improve Perceptual Learning in Connectionist Networks. | Vasant G. Honavar, Leonard Uhr |