Publications

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2015
Fakhraei, S., Foulds, J., Shashanka, M. & Getoor, L. Collective Spammer Detection in Evolving Multi-Relational Social Networks. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) (ACM, 2015).PDF icon fakhraei-kdd2015.pdf (573.89 KB)
Fakhraei, S., Onukwugha, E. & Getoor, L. Healthcare Data Analytics (Reddy, C. C. Aggarwa) (CRC Press, 2015).PDF icon fakhraei_book_2015.pdf (234.2 KB)
Rekatsinas, T., Dong, X. Luna, Getoor, L. & Srivastava, D. Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration. 7th Biennial Conference on Innovative Data Systems Research (CIDR `15) (2015).PDF icon rekatsinasCIDR15.pdf (396.99 KB)
He, X., Rekatsinas, T., Foulds, J., Getoor, L. & Liu, Y. HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades. International Conference on Machine Learning (2015).PDF icon He2015HawkesTopic.pdf (819.91 KB)
Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. ArXiv:1505.04406 [cs.LG] (2015).PDF icon bach-arxiv15.pdf (686.27 KB)
Kouki, P., Fakhraei, S., Foulds, J., Eirinaki, M. & Getoor, L. HyPER: A Flexible and Extensible Probabilistic Framework for Hybrid Recommender Systems. 9th ACM Conference on Recommender Systems (RecSys) (ACM, 2015).PDF icon kouki-recsys15.pdf (1.03 MB)
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)
Foulds, J., Kumar, S. & Getoor, L. Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models. International Conference on Machine Learning (ICML) (2015).PDF icon Foulds2015LatentTopicNetworks.pdf (382.53 KB)
Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning Journal 99, 1–45 (2015).PDF icon kimmig-mlj15.pdf (785.58 KB)
Pujara, J., London, B., Getoor, L. & Cohen, W. Online Inference for Knowledge Graph Construction. Workshop on Statistical Relational AI (2015).PDF icon pujara-starai15.pdf (340.95 KB)
Bach, S. H., Huang, B., Boyd-Graber, J. & Getoor, L. Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs. International Conference on Machine Learning (ICML) (2015).PDF icon bach-icml15.pdf (356.46 KB)
Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. RELLY: Inferring Hypernym Relationships Between Relational Phrases. Conference on Empirical Methods in Natural Language Processing (2015).PDF icon agrycner-emnlp15.pdf (234.86 KB)
Rekatsinas, T. et al. SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources. 2015 SIAM International Conference on Data Mining (SDM15) (SIAM, 2015).PDF icon rekatsinasSDM2015.pdf (303.08 KB)
London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. (2015).PDF icon london-stability15.pdf (532.16 KB)
Farnadi, G. et al. Statistical Relational Learning with Soft Quantifiers. International Conference on Inductive Logic Programming (ILP) (2015).PDF icon farnadi-ilp15.pdf (578.43 KB)
Ramesh, A., Rodriguez, M. & Getoor, L. Understanding Influence in Online Professional Networks. NIPS Workshop on Networks in Social and Information Sciences (2015).PDF icon ramesh-nipsws15.pdf (211.44 KB)
Bach, S. H., Huang, B. & Getoor, L. Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees. Artificial Intelligence and Statistics (AISTATS) (2015).PDF icon bach-aistats15.pdf (345.2 KB)
Pujara, J., Miao, H., Getoor, L. & Cohen, W. Using Semantics & Statistics to Turn Data into Knowledge. AI Magazine 36, 65–74 (2015).PDF icon pujara_aimag15.pdf (359.48 KB)
Ramesh, A., Kumar, S., Foulds, J. & Getoor, L. Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums. 53rd Annual Meeting of the Association for Computational Linguistics (ACL) (2015).PDF icon ramesh-acl15.pdf (168.7 KB)
2014
Ramakrishnan, N. et al. ‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2014).PDF icon ramakrishnan-kdd14.pdf (1.15 MB)
Pujara, J. & Getoor, L. Building Dynamic Knowledge Graphs. NIPS Workshop on Automated Knowledge Base Construction (2014).PDF icon pujara_akbc14.pdf (143.26 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., 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).
Fakhraei, S., Onukwugha, E. & Getoor, L. Healthcare Data Analytics (Reddy, C. C. Aggarwa) (CRC Press, 2014).
Farnadi, G., Bach, S. H., Moens, M. - F., Getoor, L. & De Cock, M. Extending PSL with Fuzzy Quantifiers. International Workshop on Statistical Relational Artificial Intelligence (StaRAI) (2014).PDF icon farnadi-starai14.pdf (196.15 KB)
Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Learning Latent Engagement Patterns of Students in Online Courses. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI Press, 2014).PDF icon ramesh-aaai14.pdf (505.47 KB)
Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning 1-45 (2014).
Fakhraei, S., Huang, B., Raschid, L. & Getoor, L. Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic. IEEE/ACM Transactions on Computational Biology and Bioinformatics (2014).PDF icon fakhraei-tcbb2014_accepted.pdf (3.97 MB)
London, B., Huang, B., Taskar, B. & Getoor, L. PAC-Bayesian Collective Stability. Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (2014).PDF icon london-aistats14.pdf (490.14 KB)
Bach, S. H., Huang, B. & Getoor, L. Probabilistic Soft Logic for Social Good. KDD Workshop on Data Science for Social Good (2014).PDF icon bach-dssg14.pdf (124.88 KB)
Bach, S. H., Huang, B. & Getoor, L. Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies. NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML) (2014).PDF icon bach-discml14.pdf (254.9 KB)
London, B., Huang, B. & Getoor, L. On the Strong Convexity of Variational Inference. NIPS Workshop on Advances in Variational Inference (2014).PDF icon london-nips14ws.pdf (253.72 KB)
Moustafa, W. Eldin, Kimmig, A., Deshpande, A. & Getoor, L. Subgraph Pattern Matching over Uncertain Graphs with Identity Linkage Uncertainty. International Conference on Data Engineering (ICDE) (2014).PDF icon ICDE14_conf_full_374.pdf (1.57 MB)
Bradley, S. & Getoor, L. Topic Modeling for Wikipedia Link Disambiguation. ACM Transactions on Information Systems 32, (2014).
Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs. ACM Conference on Learning at Scale (ACM, 2014).
Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Understanding MOOC Discussion Forums using Seeded LDA. 9th ACL Workshop on Innovative Use of NLP for Building Educational Applications (ACL, 2014).PDF icon ramesh-aclws14.pdf (137.57 KB)
Grycner, A., Weikum, G., Pujara, J., Foulds, J. & Getoor, L. A Unified Probabilistic Approach for Semantic Clustering of Relational Phrases. NIPS Workshop on Automated Knowledge Base Construction (2014).
2013
London, B. et al. Collective Activity Detection using Hinge-loss Markov Random Fields. CVPR Workshop on Structured Prediction: Tractability, Learning and Inference (2013).PDF icon london-cvpr13.pdf (705.87 KB)
London, B. & Getoor, L. Data Classification: Algorithms and Applications (Aggarwal, C.) (CRC Press, 2013).PDF icon cc-chapter.pdf (394.37 KB)
Fakhraei, S., Huang, B. & Getoor, L. Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction. NIPS Workshop on Machine Learning in Computational Biology (MLCB) (2013).
London, B., Huang, B., Taskar, B. & Getoor, L. Collective Stability in Structured Prediction: Generalization from One Example. Proceedings of the 30th International Conference on Machine Learning (ICML-13) (2013).PDF icon london-icml13-long.pdf (373.82 KB)
Fakhraei, S., Raschid, L. & Getoor, L. Drug-Target Interaction Prediction for Drug Repurposing with Probabilistic Similarity Logic. ACM SIGKDD 12th International Workshop on Data Mining in Bioinformatics (BIOKDD) (ACM, 2013).PDF icon FakhraeiBioKDD13.pdf (669.27 KB)
Huang, B., London, B., Taskar, B. & Getoor, L. Empirical Analysis of Collective Stability. ICML Workshop on Structured Learning (SLG) (2013).PDF icon huang-slg13.pdf (237.81 KB)
Getoor, L. & Machanavajjhala, A. Entity Resolution in Big Data. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2013).PDF icon getoor_kdd13.pdf (7.16 MB)
Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. A Flexible Framework for Probabilistic Models of Social Trust. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).PDF icon huang-sbp13.pdf (247.2 KB)
Moustafa, W. Eldin, Miao, H., Deshpande, A. & Getoor, L. GrDB: A System for Declarative and Interactive Analysis of Noisy Information Networks. ACM SIGMOD Conference (2013).PDF icon sigmod13.pdf (1.1 MB)
London, B., Huang, B. & Getoor, L. Graph-based Generalization Bounds for Learning Binary Relations. (2013).PDF icon br_risk_bounds.pdf (304.54 KB)
Bach, S. H., Huang, B., London, B. & Getoor, L. Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction. Uncertainty in Artificial Intelligence (2013).PDF icon bach-uai13.pdf (379.45 KB)
Miao, H., Liu, X., Huang, B. & Getoor, L. A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization. 2013 IEEE International Conference on Big Data (2013).PDF icon miao-bd13.pdf (307.51 KB)
Pujara, J., Miao, H. & Getoor, L. Joint Judgments with a Budget: Strategies for Reducing the Cost of Inference. ICML Workshop on Machine Learning with Test-Time Budgets (2013).PDF icon pujara_wtbudg13.pdf (221.26 KB)

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