Publications

Export 286 results:
Author Keyword Title Type [ Year(Asc)]
2018
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).
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).
Kimmig, A., Memory, A., Miller, R. & Getoor, L. A Collective, Probabilistic Approach to Schema Mapping. International Conference on Data Engineering (ICDE) (2017).
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).
Tomkins, S., Pujara, J. & Getoor, L. Disambiguating Energy Disaggregation: A Collective Probabilistic Approach. International Joint Conference on Artifi cial Intelligence (2017).
Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. Hinge-Loss Markov Random Fields and Probabilistic Soft Logic. Journal of Machine Learning Research 18, 1-67 (2017).
Ramesh, A., Rodriguez, M. & Getoor, L. Multi-relational influence models for online professional networks. International Conference on Web Intelligence (ICWI) 291-298 (ACM, 2017).
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 (International World Wide Web Conferences Steering Committee, 2017).
Farnadi, G., Bach, S. H., Moens, M. - F., Getoor, L. & De Cock, M. Soft quantification in statistical relational learning. Machine Learning Journal (2017).
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).
Kouki, P., Schaffer, J., Pujara, J., ODonovan, J. & Getoor, L. User Preferences for Hybrid Explanations. 11th ACM Conference on Recommender Systems (RecSys) (2017).
Sridhar, D., Pujara, J. & Getoor, L. Using Noisy Extractions to Discover Causal Knowledge. NIPS Workshop on Automated Knowledge Base Construction (2017).
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).
Muthiah, S., Huang, B., Arredondo, J., Mares, D. & Getoor, L. Capturing Planned Protests from Open Source Indicators. AI Magazine 37, 63–75 (2016).
Kouki, P., Marcum, C., Koehly, L. & Getoor, L. Entity Resolution in Familial Networks. 12th International Workshop on Mining and Learning with Graphs (2016).
Rekatsinas, T. et al. Forecasting Rare Disease Outbreaks from Open Source Indicators. Statistical Analysis and Data Mining: The ASA Data Science Journal (2016).
Pujara, J. & Getoor, L. Generic Statistical Relational Entity Resolution in Knowledge Graphs. Sixth International Workshop on Statistical Relational AI (IJCAI 2016, 2016).
Sridhar, D. & Getoor, L. Joint Probabilistic Inference for Causal Structure Discovery. Uncertainty in Artificial Intelligence (UAI) Workshop on Causation (2016).
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).
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).
Sridhar, D., Fakhraei, S. & Getoor, L. A Probabilistic Approach for Collective Similarity-based Drug-Drug Interaction Prediction. Bioinformatics (2016).
Ramesh, A. A Probabilistic Approach to Modeling Socio-Behavioral Interactions. (2016).
Pujara, J. Probabilistic Models for Scalable Knowledge Graph Construction. (2016).
Rekatsinas, T., Deshpande, A., Dong, X. Luna, Getoor, L. & Srivastava, D. SourceSight: Enabling Effective Source Selection. ACM SIGMOD Conference (2016).
London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. Journal of Machine Learning Research 17, (2016).

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