Publications

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2013
Kang, J., Lerman, K. & Getoor, L. LA-LDA: A Limited Attention Topic Model for Social Recommendation. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).PDF icon kang-sbp13.pdf (622.52 KB)
Pujara, J., Miao, H., Getoor, L. & Cohen, W. Large-Scale Knowledge Graph Identification using PSL. ICML Workshop on Structured Learning (SLG) (2013).PDF icon pujara_slg13.pdf (277.63 KB)
Pujara, J., Miao, H., Getoor, L. & Cohen, W. Large-Scale Knowledge Graph Identification using PSL. AAAI Fall Symposium on Semantics for Big Data (2013).PDF icon pujara_s4bd13.pdf (306.96 KB)
Bach, S. H., Huang, B. & Getoor, L. Large-margin Structured Learning for Link Ranking. NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications (2013).PDF icon bach-fna13.pdf (210.09 KB)
Bach, S. H., Huang, B. & Getoor, L. Learning Latent Groups with Hinge-loss Markov Random Fields. ICML Workshop on Inferning: Interactions between Inference and Learning (2013).PDF icon bach-inferning13.pdf (348.79 KB)
Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Modeling Learner Engagement in MOOCs using Probabilistic Soft Logic. NIPS Workshop on Data Driven Education (2013).PDF icon ramesh-nipsws13.pdf (153.92 KB)
London, B., Rekatsinas, T., Huang, B. & Getoor, L. Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss. (2013).PDF icon mrwtd.pdf (460.45 KB)
Pujara, J., Miao, H., Getoor, L. & Cohen, W. Ontology-Aware Partitioning for Knowledge Graph Identification. CIKM Workshop on Automatic Knowledge Base Construction (2013).PDF icon pujara_akbc13.pdf (370.62 KB)
London, B., Huang, B., Taskar, B. & Getoor, L. PAC-Bayes Generalization Bounds for Randomized Structured Prediction. NIP Workshop on Perturbation, Optimization and Statistics (2013).PDF icon london-nips13ws.pdf (205.57 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).
2015
London, B., Huang, B. & Getoor, L. The Benefits of Learning with Strongly Convex Approximate Inference. International Conference on Machine Learning (ICML) (2015).PDF icon london-icml15.pdf (788.06 KB)
Pujara, J., London, B. & Getoor, L. Budgeted Online Collective Inference. Uncertainty in Artificial Intelligence (2015).PDF icon pujara-uai15.pdf (302.63 KB)
Namata, G. Mark, London, B. & Getoor, L. Collective Graph Identification. ACM Transactions on Knowledge Discovery from Data 10, 25:1–25:36 (2015).PDF icon namata-tkdd.pdf (500.96 KB)
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)
2016
Fakhraei, S., Sridhar, D., Pujara, J. & Getoor, L. Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks. 12th International SIGKDD Workshop on Mining and Learning with Graphs (MLG) (ACM SIGKDD, 2016).PDF icon fakhraei_mlg_2016.pdf (711.26 KB)

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