Publications

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A
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)
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)
D
Fakhraei, S., Onukwugha, E. & Getoor, L. Healthcare Data Analytics (Reddy, C. C. Aggarwa) (CRC Press, 2014).
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)
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)
E
Friedman, N. & Getoor, L. Efficient Learning Using Constrained Sufficient Statistics. Uncertainty99 (1999).
Getoor, L., Ottosson, G., Fromherz, M. & Carlson, B. Effictive Redundant Constraints for Online Scheduling. Proceedings of the Fourteenth national Conference on Artificial Intelligence (1997).
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)
F
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)
Getoor, L., Koller, D. & Friedman, N. From Instances to Classes in Probabilistic Relational Models. Proceedings of the ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries (2000).
Getoor, L., Koller, D. & Friedman, N. From Instances to Classes in Probabilistic Relational Models. Proceedings of the ICML Workshop on Attribute-Value and Relational Learning: Crossing the Boundaries (2000).
G
Koller, D., Friedman, N., Getoor, L. & Taskar, B. An Introduction to Statistical Relational Learning (Getoor, L. & Taskar, B.) (MIT Press, 2007).PDF icon srlbook-ch2.pdf (513.11 KB)
J
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)
L
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)
Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Link Structure. Journal of Machine Learning Research 3, 679- -707 (2002).PDF icon jmlr02.pdf (502.22 KB)
Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Relational Structure. Proceedings of International Conference on Machine Learning (ICML) (2001).PDF icon icml01.pdf (157.91 KB)
Getoor, L., Friedman, N., Koller, D. & Pfeffer, A. Relational Data Mining (Dzeroski, S. & Lavrac, N.) (Springer-Verlag, 2001).
Friedman, N., Getoor, L., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. International Joint Conference on Arti cial Intelligence (1999).PDF icon icjai99.pdf (156.94 KB)
Getoor, L., Friedman, N., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. Relational Data Mining (Springer-Verlag, 2001).PDF icon lprm-ch.pdf (376 KB)
Getoor, L., Koller, D., Taskar, B. & Friedman, N. Learning Probabilistic Relational Models with Structural Uncertainty. Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data (2000).
Getoor, L., Friedman, N. & Koller, D. Learning Structured Statistical Models from Relational Data. Electronic Transactions on Artificial Intelligence 6, (2002).
Srinivasan, S., Babaki, B., Farnadi, G. & Getoor, L. Lifted Hinge-Loss Markov Random Fields. 33rd AAAI Conference on Artificial Intelligence (2019).PDF icon srinivasan-aaai19.pdf (417.5 KB)
O
Getoor, L. & Fromherz, M. Online Scheduling for Reprographic Machines. Working notes AAAI Workshop on Online Search (1997).
P
Rastegari, M., Choi, J., Fakhraei, S., III, H. Daume & Davis, L. Predictable Dual-View Hashing. Proceedings of the 30th International Conference on Machine Learning (ICML-13) 1328–1336 (JMLR, 2013).PDF icon rastegari13.pdf (2.35 MB)
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)
Getoor, L., Friedman, N., Koller, D., Pfeffer, A. & Taskar, B. An Introduction to Statistical Relational Learning (Getoor, L. & Taskar, B.) (MIT Press, 2007).PDF icon srlbook-ch5.pdf (648.15 KB)
W
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)

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