Publications

Export 317 results:
Author Title [ Year(Desc)]
2015
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)
Rekatsinas, T. Quality-Aware Data Source Management. (2015).
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)
London, B. On the Stability of Structured Prediction. (2015).PDF icon blondon-thesis.pdf (1.16 MB)
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)
Muthiah, S. et al. Capturing Planned Protests from Open Source Indicators. AI Magazine 37, 63–75 (2016).PDF icon muthiah-aimag16.pdf (1.23 MB)
Kouki, P., Marcum, C., Koehly, L. & Getoor, L. Entity Resolution in Familial Networks. 12th International Workshop on Mining and Learning with Graphs (2016).PDF icon kouki-mlg16.pdf (633.08 KB)
Rekatsinas, T. et al. Forecasting Rare Disease Outbreaks from Open Source Indicators. Statistical Analysis and Data Mining: The ASA Data Science Journal (2016).PDF icon rekatsinas-sadm17.pdf (303.08 KB)
Pujara, J. & Getoor, L. Generic Statistical Relational Entity Resolution in Knowledge Graphs. Sixth International Workshop on Statistical Relational AI (IJCAI 2016, 2016).PDF icon pujara-starai16.pdf (151.37 KB)
Sridhar, D. & Getoor, L. Joint Probabilistic Inference of Causal Structure. 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining Workshop on Causal Discovery (2016).PDF icon sridhar-kdd-ws16.pdf (204.51 KB)
Tomkins, S., Ramesh, A. & Getoor, L. Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study. International Conference on Educational Data Mining (EDM) (2016).PDF icon tomkins-edm16.pdf (619.77 KB)
Sridhar, D., Fakhraei, S. & Getoor, L. A Probabilistic Approach for Collective Similarity-based Drug-Drug Interaction Prediction. Bioinformatics (2016).PDF icon sridhar-bioinformatics_2016.pdf (1.94 MB)
Ramesh, A. A Probabilistic Approach to Modeling Socio-Behavioral Interactions. (2016).PDF icon ramesh-thesis16.pdf (865.41 KB)
Sridhar, D. & Getoor, L. Probabilistic Inference for Causal Structure Discovery. Uncertainty in Artificial Intelligence (UAI) Workshop on Causation (2016).PDF icon sridhar-uai-open-problem-v2.pdf (118.31 KB)
Pujara, J. Probabilistic Models for Scalable Knowledge Graph Construction. (2016).PDF icon pujara-thesis15.pdf (1.06 MB)
Rekatsinas, T., Deshpande, A., Dong, X. Luna, Getoor, L. & Srivastava, D. SourceSight: Enabling Effective Source Selection. ACM SIGMOD Conference (2016).PDF icon modde087.pdf (799.94 KB)
London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. Journal of Machine Learning Research 17, (2016).PDF icon london-jlmr17.pdf (532.8 KB)
Kumar, S. et al. Unsupervised Models for Predicting Strategic Relations between Organizations. IEEE ACM International Conference on Advances in Social Networks Analysis and Mining (IEEE, 2016).PDF icon kumar_asonam16.pdf (212.61 KB)
2017
Kouki, P., Pujara, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Familial Networks. IEEE International Conference on Data Mining (ICDM) (2017). at <https://github.com/pkouki/icdm2017>PDF icon kouki-icdm17.pdf (653.4 KB)
Kimmig, A., Memory, A., Miller, R. & Getoor, L. A Collective, Probabilistic Approach to Schema Mapping. International Conference on Data Engineering (ICDE) (2017). at <https://github.com/alexmemory/kimmig-icde17/wiki>PDF icon kimmig-icde17.pdf (463.69 KB)
Tomkins, S., Getoor, L., Chen, Y. & Zhang, Y. Detecting Cyber-bullying from Sparse Data and Inconsistent Labels. Learning with Limited Labeled Data (LLD) NIPS Workshop (2017).PDF icon tomkins-NIPSLLD17.pdf (286.95 KB)
Tomkins, S., Pujara, J. & Getoor, L. Disambiguating Energy Disaggregation: A Collective Probabilistic Approach. International Joint Conference on Artifi cial Intelligence (2017).PDF icon tomkins-ijcai17.pdf (373.28 KB)
Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. Journal of Machine Learning Research (JMLR) 18, 1-67 (2017).PDF icon bach-jmlr17.pdf (731.56 KB)
Ramesh, A., Rodriguez, M. & Getoor, L. Multi-relational influence models for online professional networks. International Conference on Web Intelligence (ICWI) 291-298 (ACM, 2017).PDF icon ramesh-icwi17.pdf (761.17 KB)
Kim, S., Kini, N., Pujara, J., Koh, E. & Getoor, L. Probabilistic Visitor Stitching on Cross-Device Web Logs. International Conference on World Wide Web (WWW) 1581–1589 (2017).PDF icon p1581-kimwww17.pdf (1.23 MB)
Farnadi, G., Bach, S. H., Moens, M. - F., Getoor, L. & De Cock, M. Soft quantification in statistical relational learning. Machine Learning Journal (2017).PDF icon farnadi-mlj17.pdf (1.24 MB)
Pujara, J., Augustine, E. & Getoor, L. Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short. Conference on Empirical Methods in Natural Language Processing (EMNLP) (2017). at <https://github.com/eriq-augustine/meta-kg>PDF icon pujara-emnlp17.pdf (677.74 KB)
Kouki, P., Schaffer, J., Pujara, J., ODonovan, J. & Getoor, L. User Preferences for Hybrid Explanations. 11th ACM Conference on Recommender Systems (RecSys) (2017).PDF icon kouki-recsys17.pdf (2.64 MB)
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)
2018
Embar, V., Farnadi, G., Pujara, J. & Getoor, L. Aligning Product Categories using Anchor Products. First Workshop on Knowledge Base Construction, Reasoning and Mining (2018).PDF icon embar-kbcom18.pdf (577.65 KB)
Chang, J., Chen, R., Pujara, J. & Getoor, L. Clustering System Data using Aggregate Measures. SysML (2018).PDF icon chang-sysml18.pdf (299.32 KB)
Kouki, P., Pujra, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Multi-Relational Familial Networks. Knowledge and Information Systems (KAIS) (2018).PDF icon kouki-kais18.pdf (1.17 MB)
Augustine, E. & Getoor, L. A Comparison of Bottom-Up Approaches to Grounding for Templated Markov Random Fields. SysML (2018). at <https://github.com/eriq-augustine/grounding-experiments>PDF icon augustine-sysml18.pdf (624.33 KB)
Sridhar, D., Springer, A., Hollis, V., Whittaker, S. & Getoor, L. Estimating Causal Effects of Exercise from Mood Logging Data. ICML Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action (2018).PDF icon sridhar-causalml18.pdf (333.69 KB)
Farnadi, G., Babaki, B. & Getoor, L. Fairness in Relational Domains. AAAI/ACM Conference on AI, Ethics, and Society (2018).PDF icon farnadi_aies2018.pdf (418.24 KB)
Farnadi, G., Kouki, P., Thompson, S. K., Srinivasan, S. & Getoor, L. A Fairness-aware Hybrid Recommender System. The 2nd FATREC Workshop on Responsible Recommendation (2018).PDF icon GFarnadi-FATREC2018.pdf (474.04 KB)
Farnadi, G., Babaki, B. & Getoor, L. Fairness-aware Relational Learning and Inference. Third International Workshop on Declarative Learning Based Programming (DeLBP) at thirty-second AAAI conference on Artificial Intelligence (2018).PDF icon GFarnadi-DeLBP2018.pdf (169.37 KB)
Tomkins, S., Farnadi, G., Amantullah, B., Getoor, L. & Minton, S. The Impact of Environmental Stressors on Human Trafficking. Beyond Online Data (ICWSM Workshop) (2018).PDF icon icdm_2018.pdf (473.58 KB)
Tomkins, S., Farnadi, G., Amantullah, B., Getoor, L. & Minton, S. The Impact of Environmental Stressors on Human Trafficking. International Conference on Data Mining (ICDM) (2018).PDF icon icdm_2018.pdf (473.58 KB)
Augustine, E. & Farnadi, G. MLTrain: Collective Reasoning With Probabilistic Soft Logic. (2018). at <https://github.com/linqs/psl-examples/tree/uai18>PDF icon MLTrain - UAI 2018.pdf (8.93 MB)
Kouki, P. Resolution, Recommendation, and Explanation in Richly Structured Social Networks. Technology and Information Management Ph.D. Thesis, (2018).PDF icon kouki-dissertation.pdf (6.94 MB)
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)
Embar, V., Sridhar, D., Farnadi, G. & Getoor, L. Scalable Structure Learning for Probabilistic Soft Logic. Workshop on Statistical Relational AI (2018).PDF icon VEmbar-StarAI2018.pdf (400.23 KB)

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