Export 294 results:
Author Keyword Title Type [ Year(Asc)]
Embar, V., Farnadi, G., Pujara, J. & Getoor, L. Aligning Product Categories using Anchor Products. First Workshop on Knowledge Base Construction, Reasoning and Mining (2018). (577.65 KB)
Chang, J., Chen, R., Pujara, J. & Getoor, L. Clustering System Data using Aggregate Measures. SysML (2018). (299.32 KB)
Augustine, E. & Getoor, L. A Comparison of Bottom-Up Approaches to Grounding for Templated Markov Random Fields. SysML (2018). (624.33 KB)
Farnadi, G., Babaki, B. & Getoor, L. Fairness in Relational Domains. AAAI/ACM Conference on AI, Ethics, and Society (2018). (418.24 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).
Sridhar, D., Pujara, J. & Getoor, L. Scalable Probabilistic Causal Structure Discovery. International Joint Conference on Artificial Intelligence (2018).
Zhang, Y., Ramesh, A., Golbeck, J., Sridhar, D. & Getoor, L. A Structured Approach to Understanding Recovery and Relapse in AA. The Web Conference (WWW) (2018).
Kouki, P., Pujara, J., Marcum, C., Koehly, L. & Getoor, L. Collective Entity Resolution in Familial Networks. IEEE International Conference on Data Mining (ICDM) (2017). (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). (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).
Tomkins, S., Pujara, J. & Getoor, L. Disambiguating Energy Disaggregation: A Collective Probabilistic Approach. International Joint Conference on Artifi cial Intelligence (2017). (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). (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).
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). (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).
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). (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). (2.64 MB)
Sridhar, D., Pujara, J. & Getoor, L. Using Noisy Extractions to Discover Causal Knowledge. NIPS Workshop on Automated Knowledge Base Construction (2017).
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). (711.26 KB)
Muthiah, S. et al. Capturing Planned Protests from Open Source Indicators. AI Magazine 37, 63–75 (2016). (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). (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).
Pujara, J. & Getoor, L. Generic Statistical Relational Entity Resolution in Knowledge Graphs. Sixth International Workshop on Statistical Relational AI (IJCAI 2016, 2016). (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). (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). (619.77 KB)