Publications

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Srinivasan, S., Babaki, B., Farnadi, G. & Getoor, L. Lifted Hinge-Loss Markov Random Fields. AAAI (2019).PDF icon srinivasan-aaai19.pdf (417.5 KB)
Srinivasan, S., Rao, N. S., Subbaian, K. & Getoor, L. Identifying Facet Mismatches In Search Via Micrographs. CIKM (2019).PDF icon srinivasan-cikm19.pdf (887.06 KB)
Srinivasan, S., Farnadi, G. & Getoor, L. BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic. Association for the Advancement of Artificial Intelligence (2020).PDF icon srinivasan-aaai20a.pdf (478.67 KB)
Srinivasan, S., Augustine, E. & Getoor, L. Tandem Inference: An Out-of-Core Streaming Algorithm For Very Large-Scale Relational Inference. Association for the Advancement of Artificial Intelligence (2020).PDF icon srinivasan-aaai20b.pdf (506.62 KB)
Sridhar, D., Getoor, L. & Walker, M. Collective Stance Classification of Posts in Online Debate Forums. ACL Joint Workshop on Social Dynamics and Personal Attributes in Social Media (2014).PDF icon sridhar-aclws14.pdf (190.8 KB)
Sridhar, D., Pujara, J. & Getoor, L. Using Noisy Extractions to Discover Causal Knowledge. NIPS Workshop on Automated Knowledge Base Construction (2017).PDF icon sridhar-akbc17.pdf (203.34 KB)
Sridhar, D., Foulds, J., Walker, M., Huang, B. & Getoor, L. Joint Models of Disagreement and Stance in Online Debate. Annual Meeting of the Association for Computational Linguistics (ACL) (2015).PDF icon sridhar-acl15.pdf (227.14 KB)
Sridhar, D. & Getoor, L. Joint Probabilistic Inference of Causal Structure. KDD Workshop on CD (2016).PDF icon sridhar-cd16.pdf (204.51 KB)
Sridhar, D. & Getoor, L. Probabilistic Inference for Causal Structure Discovery. UAI Workshop on Causation (2016).PDF icon sridhar-causation16.pdf (118.31 KB)
Sridhar, D., Fakhraei, S. & Getoor, L. A Probabilistic Approach for Collective Similarity-based Drug-Drug Interaction Prediction. Bioinformatics 32, (2016).PDF icon sridhar-bioinformatics16.pdf (1.94 MB)
Sridhar, D., Foulds, J., Huang, B., Walker, M. & Getoor, L. Collective classification of stance and disagreement in online debate forums. Bay Area Machine Learning Symposium (BayLearn) (2014).
Sridhar, D., Pujara, J. & Getoor, L. Scalable Probabilistic Causal Structure Discovery. International Joint Conference on Artificial Intelligence (2018). at <https://bitbucket.org/linqs/causpsl/src/master/>PDF icon sridhar-ijcai18.pdf (281.32 KB)
Sridhar, D., Springer, A., Hollis, V., Whittaker, S. & Getoor, L. Estimating Causal Effects of Exercise from Mood Logging Data. ICML Workshop on CausalML (2018).PDF icon sridhar-causalml18.pdf (333.69 KB)
Sridhar, D. & Getoor, L. Estimating Causal Effects of Tone in Online Debates. IJCAI (2019).PDF icon sridhar-ijcai19.pdf (220.49 KB)
Somasundaran, S., Namata, G. Mark, Getoor, L. & Wiebe, J. Opinion Graphs for Polarity and Discourse Classification. TextGraphs-4: Graph-based Methods for Natural Language Processing (2009).PDF icon somasundaran-textgraphs09.pdf (289.75 KB)
Somasundaran, S., Namata, G. Mark, Wiebe, J. & Getoor, L. Supervised and Unsupervised Methods in Employing Discourse Relations for Improving Opinion Polarity Classification. Conference on Empirical Methods in Natural Language Processing (2009).PDF icon somasundaran-emnlp09.pdf (390.93 KB)
Smith, M., Barash, V., Getoor, L. & Lauw, H. Leveraging Social Context for Searching Social Media. CIKM Workshop on Search in Social Media (2008).
Singh, L. & Getoor, L. Increasing the predictive power of affiliation networks. IEEE Data Engineering Bulletin 30, (2007).PDF icon singh.pdf (87.94 KB)
Singh, L., Beard, M., Getoor, L. & M. Blake, B. Visual mining of multi-modal social networks at different abstraction levelsx. L. Singh, M. Beard, L. Getoor, M. Blake. Visual mining of multi-modal social networks at different abstraction levels. IEEE Conference on Information Visualization - Symposium of Visual Data Mining (IV-VDM) (2007).PDF icon singh2007IV.pdf (809.15 KB)
Singh, L., Getoor, L. & Licamele, L. Pruning Social Networks Using Structural Properties and Descriptive Attributes. IEEE International Conference on Data Mining (ICDM) 773-776 (2005).PDF icon singh_icdm05.pdf (149.45 KB)
Sharara, H., Singh, L. & Getoor, L. Finding Prominent Actors in Dynamic Affiliation Networks. Human Journal (2012).PDF icon 105-204-1-SM.pdf (757.7 KB)
Sharara, H., Rand, W. & Getoor, L. Differential Adaptive Diffusion: Understanding Diversity and Learning whom to Trust in Viral Marketing. ICWSM (2011).PDF icon sharara-aaai11.pdf (646.6 KB)
Sharara, H., Sopan, A., Namata, G. Mark, Getoor, L. & Singh, L. G-PARE: A Visual Analytic Tool for Comparative Analysis of Uncertain Graphs. IEEE Conference on Visual Analytics Science and Technology (VAST) (2011).PDF icon sharara-vast11.pdf (1.64 MB)
Sharara, H., Halgin, D., Getoor, L. & Borgatti, S. Multi-dimensional Trajectory Analysis for Career Histories. International Sunbelt Social Networks Conference (Sunbelt XXXI) (2011).
Sharara, H., Singh, L., Getoor, L. & Mann, J. Understanding Actor Loyalty to Event-Based Groups in Affiliation Networks. Journal of Advances in Social Networks Analysis and Mining 1, 115–126 (2011).
Sharara, H., Getoor, L. & Norton, M. Active Surveying. NIPS Workshop on Networks Across Disciplines in Theory and Applications (2010).
Sharara, H., Norton, M. & Getoor, L. Active Surveying for Leadership Identification. The International Sunbelt Social Networks Conference XXX (2010).
Sharara, H., Getoor, L. & Norton, M. An Active Learning Approach for Identifying Key Opinion Leaders. The 2nd Workshop on Information in Networks (WIN) (2010).
Sharara, H. & Getoor, L. Group Detection. Encyclopedia of Machine Learning (2010).
Sharara, H., Singh, L., Getoor, L. & Mann, J. The Dynamics of Actor Loyalty to Groups in Affiliation Networks. International Conference on Advances in Social Networks Analysis and Mining (2009).PDF icon sharara_asonam09.pdf (446.61 KB)
Sen, P., Namata, G. Mark, Bilgic, M. & Getoor, L. Collective Classification. Encyclopedia of Machine Learning (2010).
Sen, P., Deshpande, A. & Getoor, L. Read-Once Functions and Query Evaluation in Probabilistic Databases. International Conference on Very Large Data Bases (2010).PDF icon draft.pdf (322 KB)
Sen, P., Deshpande, A. & Getoor, L. Bisimulation-based Approximate Lifted Inference. Uncertainty in Artificial Intelligence (2009).PDF icon uai09.pdf (240.89 KB)
Sen, P., Deshpande, A. & Getoor, L. PrDB: Managing and Exploiting Rich Correlations in Probabilistic Databases. VLDB Journal, special issue on uncertain and probabilistic databases (2009).PDF icon sen-vldbj09.pdf (1.12 MB)
Sen, P. Representing and Querying Uncertain Data. (2009).PDF icon thesis.pdf (1.12 MB)
Sen, P. et al. Collective Classification in Network Data. AI Magazine 29, 93–106 (2008).PDF icon sen-aimag08.pdf (497.82 KB)
Sen, P. & Getoor, L. Cost-Sensitive Learning with Conditional Markov Networks. Data Mining and Knowledge Discovery, Special Issue on Utility Based Data Mining 17, 136–163 (2008).PDF icon draft.pdf (424.09 KB)
Sen, P., Deshpande, A. & Getoor, L. Exploiting Shared Correlations in Probabilistic Databases. International Conference on Very Large Data Bases (2008).PDF icon sen-vldb08.pdf (232.29 KB)
Sen, P. & Getoor, L. Link-based Classification. (2007).PDF icon senum-tr07.pdf (511.11 KB)
Sen, P. & Deshpande, A. Representing and Querying Correlated Tuples in Probabilistic Databases. International Conference on Data Engineering (2007).PDF icon icde07_final.pdf (309.63 KB)
Sen, P., Deshpande, A. & Getoor, L. Representing Tuple and Attribute Uncertainty in Probabilistic Databases. Workshop on Data Mining of Uncertain Data (ICDM) (2007).PDF icon dune07.pdf (176.67 KB)
Sen, P. & Getoor, L. Cost-Sensitive Learning with Conditional Markov Networks. SIAM Data Mining Workshop on Link Analysis, Counterterrorism and Security (2006).PDF icon sensiam_lacs06.pdf (137.37 KB)
Sen, P. & Getoor, L. Cost-Sensitive Learning with Conditional Markov Networks. International Conference on Machine Learning (2006).PDF icon senicml06.pdf (118.33 KB)
Sen, P. & Getoor, L. Empirical Comparison of Approximate Inference Algorithms for Networked Data. ICML Workshop on Statistical Relational Learning (SRL) (2006).PDF icon sensrl06.pdf (225.32 KB)
Sehgal, V., Getoor, L. & Viechnicki, P. Entity Resolution in Geospatial Data Integration. ACM GIS (2006).
Schnaitter, K., Polyzotis, N. & Getoor, L. Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications. International Conference on Very Large Data Bases (2009).PDF icon schnaitter-vldb09.pdf (743.29 KB)
Sayyadi, H. & Getoor, L. Future Rank: Ranking Scientific Articles by Predicting their Future PageRank. 2009 SIAM International Conference on Data Mining (SDM09) (2009).PDF icon sayyadi_futureRank_sdm09.pdf (621.55 KB)
Saha, B. & Getoor, L. On Maximum Coverage in the Streaming Model & Application to Multi-topic Blog-Watch. 2009 SIAM International Conference on Data Mining (SDM09) (2009).PDF icon saha-sdm08.pdf (233.12 KB)
Saha, B. & Getoor, L. Group Proximity Measure for Recommending Groups in Online Social Networks. 2nd ACM SIGKDD Workshop on Social Network Mining and Analysis (SNA-KDD) (2008).PDF icon kddw-saha.pdf (311.36 KB)