default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDVasant G. Honavar
Person information
- affiliation: Pennsylvania State University, University Park, Pennsylvania, USA
- affiliation: Iowa State University, Ames, Iowa, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[c178]Junjie Liang, Weijieying Ren, Hanifi Sahar, Vasant G. Honavar
:
Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data. AAAI 2024: 13736-13743- [c177]Abhishek Dalvi, Neil Ashtekar, Vasant G. Honavar:
Causal Matching using Random Hyperplane Tessellations. CLeaR 2024: 688-702 - [c176]Weijieying Ren, Xiaoting Li, Huiyuan Chen, Vineeth Rakesh, Zhuoyi Wang, Mahashweta Das, Vasant G. Honavar:
TabLog: Test-Time Adaptation for Tabular Data Using Logic Rules. ICML 2024 - [c175]Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G. Honavar:
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. ICML 2024 - [c174]Weijieying Ren, Vasant G. Honavar:
EsaCL: An Efficient Continual Learning Algorithm. SDM 2024: 163-171 - [i34]Weijieying Ren, Vasant G. Honavar:
EsaCL: Efficient Continual Learning of Sparse Models. CoRR abs/2401.05667 (2024) - [i33]Abhishek Dalvi, Vasant G. Honavar:
One-Shot Graph Representation Learning Using Hyperdimensional Computing. CoRR abs/2402.17073 (2024) - [i32]Huaisheng Zhu, Teng Xiao, Vasant G. Honavar:
3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs. CoRR abs/2403.07179 (2024) - [i31]Teng Xiao, Chao Cui, Huaisheng Zhu, Vasant G. Honavar:
MolBind: Multimodal Alignment of Language, Molecules, and Proteins. CoRR abs/2403.08167 (2024) - [i30]Abhishek Dalvi, Neil Ashtekar, Vasant G. Honavar:
Causal Effect Estimation Using Random Hyperplane Tessellations. CoRR abs/2404.10907 (2024) - 2023
- [j59]Amogh Subbakrishna Adishesha, Lily Jakielaszek, Fariha Azhar, Peixuan Zhang, Vasant G. Honavar, Fenglong Ma, Chandra Belani, Prasenjit Mitra, Sharon Xiaolei Huang:
Forecasting User Interests Through Topic Tag Predictions in Online Health Communities. IEEE J. Biomed. Health Informatics 27(7): 3645-3656 (2023) - [c173]Samik Basu, Vasant G. Honavar, Ganesh Ram Santhanam, Jia Tao:
Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries. ECAI 2023: 206-213 - [c172]Neil Ashtekar, Vasant G. Honavar:
A Simple, Fast Algorithm for Continual Learning from High-Dimensional Data. Tiny Papers @ ICLR 2023 - [i29]Samik Basu, Vasant G. Honavar, Ganesh Ram Santhanam, Jia Tao:
Representing and Reasoning with Multi-Stakeholder Qualitative Preference Queries. CoRR abs/2307.16307 (2023) - 2022
- [j58]Michael G. Kallitsis, Rupesh Prajapati, Vasant G. Honavar, Dinghao Wu, John Yen:
Detecting and Interpreting Changes in Scanning Behavior in Large Network Telescopes. IEEE Trans. Inf. Forensics Secur. 17: 3611-3625 (2022) - [i28]Amogh Subbakrishna Adishesha, Lily Jakielaszek, Fariha Azhar, Peixuan Zhang, Vasant G. Honavar, Fenglong Ma, Chandra Belani, Prasenjit Mitra, Sharon Xiaolei Huang:
Forecasting User Interests Through Topic Tag Predictions in Online Health Communities. CoRR abs/2211.02789 (2022) - 2021
- [c171]Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant G. Honavar:
Longitudinal Deep Kernel Gaussian Process Regression. AAAI 2021: 8556-8564 - [c170]Rupesh Prajapati, Vasant G. Honavar, Dinghao Wu, John Yen, Michalis Kallitsis:
Shedding light into the darknet: scanning characterization and detection of temporal changes. CoNEXT 2021: 469-470 - [c169]Junjie Liang, Wenbo Guo, Tongbo Luo, Vasant G. Honavar, Gang Wang, Xinyu Xing:
FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data. NDSS 2021 - [c168]Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, Vasant G. Honavar:
Functional Autoencoders for Functional Data Representation Learning. SDM 2021: 666-674 - [c167]Tsung-Yu Hsieh, Suhang Wang, Yiwei Sun, Vasant G. Honavar:
Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns to Attend to Important Variables As Well As Time Intervals. WSDM 2021: 607-615 - [c166]Tsung-Yu Hsieh, Yiwei Sun, Xianfeng Tang, Suhang Wang, Vasant G. Honavar:
SrVARM: State Regularized Vector Autoregressive Model for Joint Learning of Hidden State Transitions and State-Dependent Inter-Variable Dependencies from Multi-variate Time Series. WWW 2021: 2270-2280 - [i27]Michalis Kallitsis, Vasant G. Honavar, Rupesh Prajapati, Dinghao Wu, John Yen:
Zooming Into the Darknet: Characterizing Internet Background Radiation and its Structural Changes. CoRR abs/2108.00079 (2021) - 2020
- [j57]Cunliang Geng, Yong Jung, Nicolas Renaud, Vasant G. Honavar, Alexandre M. J. J. Bonvin, Li C. Xue:
iScore: a novel graph kernel-based function for scoring protein-protein docking models. Bioinform. 36(1): 112-121 (2020) - [j56]Manish Parashar, Anthony Simonet, Ivan Rodero, Forough Ghahramani, Grace Agnew, Ron Jantz, Vasant G. Honavar:
The Virtual Data Collaboratory: A Regional Cyberinfrastructure for Collaborative Data-Driven Research. Comput. Sci. Eng. 22(3): 79-92 (2020) - [j55]Nicolas Renaud, Yong Jung, Vasant G. Honavar, Cunliang Geng, Alexandre M. J. J. Bonvin, Li C. Xue:
iScore: An MPI supported software for ranking protein-protein docking models based on a random walk graph kernel and support vector machines. SoftwareX 11: 100462 (2020) - [c165]Junjie Liang, Dongkuan Xu, Yiwei Sun, Vasant G. Honavar:
LMLFM: Longitudinal Multi-Level Factorization Machine. AAAI 2020: 4811-4818 - [c164]Aria Khademi, Vasant G. Honavar:
Algorithmic Bias in Recidivism Prediction: A Causal Perspective (Student Abstract). AAAI 2020: 13839-13840 - [c163]Thanh Le, Vasant G. Honavar:
Dynamical Gaussian Process Latent Variable Model for Representation Learning from Longitudinal Data. FODS 2020: 183-188 - [c162]Yiwei Sun, Suhang Wang, Xianfeng Tang, Tsung-Yu Hsieh, Vasant G. Honavar:
Adversarial Attacks on Graph Neural Networks via Node Injections: A Hierarchical Reinforcement Learning Approach. WWW 2020: 673-683 - [i26]Junjie Liang, Yanting Wu, Dongkuan Xu, Vasant G. Honavar:
Longitudinal Deep Kernel Gaussian Process Regression. CoRR abs/2005.11770 (2020) - [i25]Aria Khademi, Vasant G. Honavar:
A Causal Lens for Peeking into Black Box Predictive Models: Predictive Model Interpretation via Causal Attribution. CoRR abs/2008.00357 (2020) - [i24]Christopher Seto, Aria Khademi, Corina Graif, Vasant G. Honavar:
Commuting Network Spillovers and COVID-19 Deaths Across US Counties. CoRR abs/2010.01101 (2020) - [i23]Tsung-Yu Hsieh, Suhang Wang, Yiwei Sun, Vasant G. Honavar:
Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time Intervals. CoRR abs/2011.11631 (2020)
2010 – 2019
- 2019
- [c161]Saravanan Kandasamy, Arnab Bhattacharyya, Vasant G. Honavar:
Minimum Intervention Cover of a Causal Graph. AAAI 2019: 2876-2885 - [c160]Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, Vasant G. Honavar:
Adaptive Structural Co-regularization for Unsupervised Multi-view Feature Selection. ICBK 2019: 87-96 - [c159]Yiwei Sun, Suhang Wang, Tsung-Yu Hsieh, Xianfeng Tang, Vasant G. Honavar:
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding. IJCAI 2019: 3527-3533 - [c158]Sanghack Lee, Vasant G. Honavar:
Towards Robust Relational Causal Discovery. UAI 2019: 345-355 - [c157]Yimin Zhou, Yiwei Sun, Vasant G. Honavar:
Improving Image Captioning by Leveraging Knowledge Graphs. WACV 2019: 283-293 - [c156]Aria Khademi, Sanghack Lee, David Foley, Vasant G. Honavar:
Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. WWW 2019: 2907-2914 - [i22]Yimin Zhou, Yiwei Sun, Vasant G. Honavar:
Improving Image Captioning by Leveraging Knowledge Graphs. CoRR abs/1901.08942 (2019) - [i21]Aria Khademi, Sanghack Lee, David Foley, Vasant G. Honavar:
Fairness in Algorithmic Decision Making: An Excursion Through the Lens of Causality. CoRR abs/1903.11719 (2019) - [i20]Yiwei Sun, Suhang Wang, Tsung-Yu Hsieh, Xianfeng Tang, Vasant G. Honavar:
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding. CoRR abs/1909.01084 (2019) - [i19]Yiwei Sun, Suhang Wang, Xianfeng Tang, Tsung-Yu Hsieh, Vasant G. Honavar:
Node Injection Attacks on Graphs via Reinforcement Learning. CoRR abs/1909.06543 (2019) - [i18]Thanh Le, Vasant G. Honavar:
The Dynamical Gaussian Process Latent Variable Model in the Longitudinal Scenario. CoRR abs/1909.11630 (2019) - [i17]Junjie Liang, Dongkuan Xu, Yiwei Sun, Vasant G. Honavar:
LMLFM: Longitudinal Multi-Level Factorization Machine. CoRR abs/1911.04062 (2019) - [i16]Aria Khademi, Vasant G. Honavar:
Algorithmic Bias in Recidivism Prediction: A Causal Perspective. CoRR abs/1911.10640 (2019) - [i15]Sanghack Lee, Vasant G. Honavar:
Towards Robust Relational Causal Discovery. CoRR abs/1912.02390 (2019) - 2018
- [j54]Jinlong Hu, Junjie Liang, Yuezhen Kuang, Vasant G. Honavar:
A user similarity-based Top-N recommendation approach for mobile in-application advertising. Expert Syst. Appl. 111: 51-60 (2018) - [c155]Mostafa M. Abbas, Thanh Le, Halima Bensmail, Vasant G. Honavar, Yasser El-Manzalawy:
Microbiomarkers Discovery in Inflammatory Bowel Diseases using Network-Based Feature Selection. BCB 2018: 172-177 - [c154]Aria Khademi, Yasser El-Manzalawy, Orfeu M. Buxton, Vasant G. Honavar:
Toward personalized sleep-wake prediction from actigraphy. BHI 2018: 414-417 - [c153]Junjie Liang, Jinlong Hu, Shoubin Dong, Vasant G. Honavar:
Top-N-Rank: A Scalable List-wise Ranking Method for Recommender Systems. IEEE BigData 2018: 1052-1058 - [c152]Yiwei Sun, Ngot Bui, Tsung-Yu Hsieh, Vasant G. Honavar:
Multi-view Network Embedding via Graph Factorization Clustering and Co-regularized Multi-view Agreement. ICDM Workshops 2018: 1006-1013 - [c151]Tsung-Yu Hsieh, Yasser El-Manzalawy, Yiwei Sun, Vasant G. Honavar:
Compositional Stochastic Average Gradient for Machine Learning and Related Applications. IDEAL (1) 2018: 740-752 - [c150]Shlomit Gur, Vasant G. Honavar:
PATENet: Pairwise Alignment of Time Evolving Networks. MLDM (1) 2018: 85-98 - [e9]Robert Dyer, Vasant G. Honavar, Gary T. Leavens, Hoan Anh Nguyen, Tien N. Nguyen, Hridesh Rajan:
Proceedings of the 1st ACM SIGSOFT International Workshop on Automated Specification Inference, WASPI@ESEC/SIGSOFT FSE, Lake Buena Vista, FL, USA, November 9, 2018. ACM 2018, ISBN 978-1-4503-6057-9 [contents] - [r3]Cornelia Caragea, Vasant G. Honavar:
Machine Learning in Computational Biology. Encyclopedia of Database Systems (2nd ed.) 2018 - [i14]Tsung-Yu Hsieh, Yasser El-Manzalawy, Yiwei Sun, Vasant G. Honavar:
Compositional Stochastic Average Gradient for Machine Learning and Related Applications. CoRR abs/1809.01225 (2018) - [i13]Yiwei Sun, Ngot Bui, Tsung-Yu Hsieh, Vasant G. Honavar:
Multi-View Network Embedding Via Graph Factorization Clustering and Co-Regularized Multi-View Agreement. CoRR abs/1811.02616 (2018) - [i12]Junjie Liang, Jinlong Hu, Shoubin Dong, Vasant G. Honavar:
Top-N-Rank: A Scalable List-wise Ranking Method for Recommender Systems. CoRR abs/1812.04109 (2018) - 2017
- [j53]Li C. Xue, João P. G. L. M. Rodrigues, Drena Dobbs, Vasant G. Honavar, Alexandre M. J. J. Bonvin:
Template-based protein-protein docking exploiting pairwise interfacial residue restraints. Briefings Bioinform. 18(3): 458-466 (2017) - [c149]Yasser El-Manzalawy, Orfeu M. Buxton, Vasant G. Honavar:
Sleep/wake state prediction and sleep parameter estimation using unsupervised classification via clustering. BIBM 2017: 718-723 - [c148]Sanghack Lee, Vasant G. Honavar:
Self-Discrepancy Conditional Independence Test. UAI 2017 - [c147]Sanghack Lee, Vasant G. Honavar:
Towards Conditional Independence Test for Relational Data. UAI 2017 - [i11]Solon Barocas, Elizabeth Bradley, Vasant G. Honavar, Foster J. Provost:
Big Data, Data Science, and Civil Rights. CoRR abs/1706.03102 (2017) - [i10]Vasant G. Honavar, Katherine A. Yelick, Klara Nahrstedt, Holly E. Rushmeier, Jennifer Rexford, Mark D. Hill, Elizabeth Bradley, Elizabeth D. Mynatt:
Advanced Cyberinfrastructure for Science, Engineering, and Public Policy. CoRR abs/1707.00599 (2017) - [i9]Gregory D. Hager, Randal E. Bryant, Eric Horvitz, Maja J. Mataric, Vasant G. Honavar:
Advances in Artificial Intelligence Require Progress Across all of Computer Science. CoRR abs/1707.04352 (2017) - 2016
- [b1]Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
Representing and Reasoning with Qualitative Preferences: Tools and Applications. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2016, ISBN 978-3-031-00445-2 - [j52]Ngot Bui, John Yen, Vasant G. Honavar:
Temporal Causality Analysis of Sentiment Change in a Cancer Survivor Network. IEEE Trans. Comput. Soc. Syst. 3(2): 75-87 (2016) - [c146]Sanghack Lee, Vasant G. Honavar:
On Learning Causal Models from Relational Data. AAAI 2016: 3263-3270 - [c145]Ngot Bui, Thanh Le, Vasant G. Honavar:
Labeling actors in multi-view social networks by integrating information from within and across multiple views. IEEE BigData 2016: 616-625 - [c144]Drena Dobbs, Steven E. Brenner, Vasant G. Honavar, Robert L. Jernigan, Alain Laederach, Quaid Morris:
Session Introduction. PSB 2016: 429-432 - [c143]Sanghack Lee, Vasant G. Honavar:
A Characterization of Markov Equivalence Classes of Relational Causal Models under Path Semantics. UAI 2016 - [i8]Vasant G. Honavar, Mark D. Hill, Katherine A. Yelick:
Accelerating Science: A Computing Research Agenda. CoRR abs/1604.02006 (2016) - 2015
- [c142]Harris T. Lin, Ngot Bui, Vasant G. Honavar:
Learning classifiers from remote RDF data stores augmented with RDFS subclass hierarchies. IEEE BigData 2015: 1807-1813 - [c141]Vasant G. Honavar:
Discovery Informatics in Biological and Biomedical Sciences: Research Challenges and Opportunities. Pacific Symposium on Biocomputing 2015: 482 - [c140]Ngot Bui, John Yen, Vasant G. Honavar:
Temporal Causality of Social Support in an Online Community for Cancer Survivors. SBP 2015: 13-23 - [c139]Sanghack Lee, Vasant G. Honavar:
Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning. ACI@UAI 2015: 56-65 - [i7]Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
CRISNER: A Practically Efficient Reasoner for Qualitative Preferences. CoRR abs/1507.08559 (2015) - [i6]Sanghack Lee, Vasant G. Honavar:
Lifted Representation of Relational Causal Models Revisited: Implications for Reasoning and Structure Learning. CoRR abs/1508.02103 (2015) - 2014
- [j51]Jia Tao, Giora Slutzki, Vasant G. Honavar:
A Conceptual Framework for Secrecy-preserving Reasoning in Knowledge Bases. ACM Trans. Comput. Log. 16(1): 3:1-3:32 (2014) - [c138]Kannan Sankar, Rasna R. Walia, Carla M. Mann, Robert L. Jernigan, Vasant G. Honavar, Drena Dobbs:
An analysis of conformational changes upon RNA-protein binding. BCB 2014: 592-593 - [c137]Ngot Bui, Vasant G. Honavar:
Labeling Actors in Social Networks Using a Heterogeneous Graph Kernel. SBP 2014: 27-34 - [e8]Jimmy Lin, Jian Pei, Xiaohua Hu, Wo Chang, Raghunath Nambiar, Charu C. Aggarwal, Nick Cercone, Vasant G. Honavar, Jun Huan, Bamshad Mobasher, Saumyadipta Pyne:
2014 IEEE International Conference on Big Data (IEEE BigData 2014), Washington, DC, USA, October 27-30, 2014. IEEE Computer Society 2014, ISBN 978-1-4799-5665-4 [contents] - [i5]Facundo Bromberg, Dimitris Margaritis, Vasant G. Honavar:
Efficient Markov Network Structure Discovery Using Independence Tests. CoRR abs/1401.3478 (2014) - [i4]Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
Representing and Reasoning with Qualitative Preferences for Compositional Systems. CoRR abs/1401.3899 (2014) - 2013
- [c136]Sanghack Lee, Vasant G. Honavar:
m-Transportability: Transportability of a Causal Effect from Multiple Environments. AAAI 2013: 583-590 - [c135]Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
Verifying Preferential Equivalence and Subsumption via Model Checking. ADT 2013: 324-335 - [c134]Ngot Bui, Vasant G. Honavar:
On the utility of abstraction in labeling actors in social networks. ASONAM 2013: 692-698 - [c133]Harris T. Lin, Vasant G. Honavar:
Learning Classifiers from Chains of Multiple Interlinked RDF Data Stores. BigData Congress 2013: 94-101 - [c132]Harris T. Lin, Sanghack Lee, Ngot Bui, Vasant G. Honavar:
Learning Classifiers from Distributional Data. BigData Congress 2013: 302-309 - [c131]Letao Qi, Harris T. Lin, Vasant G. Honavar:
Clustering remote RDF data using SPARQL update queries. ICDE Workshops 2013: 236-242 - [c130]Elias Bareinboim, Sanghack Lee, Vasant G. Honavar, Judea Pearl:
Transportability from Multiple Environments with Limited Experiments. NIPS 2013: 136-144 - [c129]Sanghack Lee, Vasant G. Honavar:
Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability. UAI 2013 - [c128]Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
Preference Based Service Adaptation Using Service Substitution. Web Intelligence 2013: 487-493 - [i3]Sanghack Lee, Vasant G. Honavar:
Causal Transportability of Experiments on Controllable Subsets of Variables: z-Transportability. CoRR abs/1309.6842 (2013) - 2012
- [j50]Rafael A. Jordan, Yasser El-Manzalawy, Drena Dobbs, Vasant G. Honavar:
Predicting protein-protein interface residues using local surface structural similarity. BMC Bioinform. 13: 41 (2012) - [j49]Rasna R. Walia, Cornelia Caragea, Benjamin A. Lewis, Fadi Towfic, Michael Terribilini, Yasser El-Manzalawy, Drena Dobbs, Vasant G. Honavar:
Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. BMC Bioinform. 13: 89 (2012) - [j48]Fadi Towfic, Shakti Gupta, Vasant G. Honavar, Shankar Subramaniam:
B-cell Ligand Processing Pathways Detected by Large-scale Comparative Analysis. Genom. Proteom. Bioinform. 10(3): 142-152 (2012) - [j47]Jia Tao, Giora Slutzki, Vasant G. Honavar:
PSPACE Tableau Algorithms for Acyclic Modalized $\boldsymbol{\mathcal{ALC}}$. J. Autom. Reason. 49(4): 551-582 (2012) - [c127]Yasser El-Manzalawy, Drena Dobbs, Vasant G. Honavar:
Predicting protective bacterial antigens using random forest classifiers. BCB 2012: 426-433 - [c126]Vasant G. Honavar:
Learning predictive models from large distributed autonomous data sources. CIDU 2012: 1 - [c125]Kewei Tu, Vasant G. Honavar:
Unambiguity Regularization for Unsupervised Learning of Probabilistic Grammars. EMNLP-CoNLL 2012: 1324-1334 - [c124]Zachary J. Oster, Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
Model Checking of Qualitative Sensitivity Preferences to Minimize Credential Disclosure. FACS 2012: 205-223 - 2011
- [j46]Li C. Xue, Drena Dobbs, Vasant G. Honavar:
HomPPI: A Class of Sequence Homology Based Protein-Protein Interface Prediction Methods. BMC Bioinform. 12: 244 (2011) - [j45]Usha Muppirala, Vasant G. Honavar, Drena Dobbs:
Predicting RNA-Protein Interactions Using Only Sequence Information. BMC Bioinform. 12: 489 (2011) - [j44]Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
Representing and Reasoning with Qualitative Preferences for Compositional Systems. J. Artif. Intell. Res. 42: 211-274 (2011) - [j43]Benjamin A. Lewis, Rasna R. Walia, Michael Terribilini, Jeff Ferguson, Charles Zheng, Vasant G. Honavar, Drena Dobbs:
PRIDB: a protein-RNA interface database. Nucleic Acids Res. 39(Database-Issue): 277-282 (2011) - [j42]Yasser El-Manzalawy, Drena Dobbs, Vasant G. Honavar:
Predicting MHC-II Binding Affinity Using Multiple Instance Regression. IEEE ACM Trans. Comput. Biol. Bioinform. 8(4): 1067-1079 (2011) - [c123]Ganesh Ram Santhanam, Yuly Suvorov, Samik Basu, Vasant G. Honavar:
Verifying Intervention Policies to Counter Infection Propagation over Networks: A Model Checking Approach. AAAI 2011: 1408-1414 - [c122]Ganesh Ram Santhanam, Samik Basu, Vasant G. Honavar:
Identifying Sustainable Designs Using Preferences over Sustainability Attributes. AAAI Spring Symposium: Artificial Intelligence and Sustainable Design 2011 - [c121]Li C. Xue, Rafael A. Jordan, Yasser El-Manzalawy, Drena Dobbs, Vasant G. Honavar:
Ranking docked models of protein-protein complexes using predicted partner-specific protein-protein interfaces: a preliminary study. BCB 2011: 441-445 - [c120]Li C. Xue, Rasna R. Walia, Yasser El-Manzalawy, Drena Dobbs, Vasant G. Honavar:
Improving protein-RNA interface prediction by combining sequence homology based method with a naive Bayes classifier: preliminary results. BCB 2011: 556-558 - [c119]Adrian Silvescu, Vasant G. Honavar:
Abstraction Super-Structuring Normal Forms: Towards a Theory of Structural Induction. Algorithmic Probability and Friends 2011: 339-350 - [c118]Oksana Yakhnenko, Vasant G. Honavar