Publications

Export 312 results:
[ Author(Asc)] Title Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
G
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).
Getoor, L. & Machanavajjhala, A. Entity Resolution in Big Data. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2013).PDF icon getoor_kdd13.pdf (7.16 MB)
Getoor, L. & Machanavajjhala, A. Entity Resolution for Social Network Analysis and Mining. IEEE ACM International Conference on Advances in Social Networks Analysis and Mining (IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2012).
Getoor, L. & Machanavajjhala, A. Entity Resolution: Theory, Practice & Open Challenges. International Conference on Very Large Data Bases (2012).PDF icon p2018_lisegetoor_vldb2012.pdf (89.45 KB)
Getoor, L. & Machanavajjhala, A. Entity Resolution: Theory, Practice, and Open Challenges. AAAI Conference on Artificial Intelligence (2012).
Getoor, L. & Mihalkova, L. Exploiting Statistical and Relational Information on the Web and in Social Media. (2011).PDF icon getoor-sdm11.pdf (88.88 KB)
Getoor, L. & Scheffer, T. Proceedings of the 28th International Conference on Machine Learning. Proceedings of the 28th International Conference on Machine Learning (2011).
Getoor, L. & Taskar, B. Introduction to Statistical Relational Learning. (The MIT Press, 2007).
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)
Getoor, L. An Introduction to Probabilistic Graphical Models for Relational Data. Data Engineering Bulletin 29, (2006).
Getoor, L. & Grant, J. PRL: A Logical Approach to Probabilistic Relational Models. Machine Learning Journal 62, (2006).PDF icon getoor-mlj06.pdf (685.04 KB)
Getoor, L. & Diehl, C. Link Mining: A Survey. SigKDD Explorations Special Issue on Link Mining 7, (2005).
Getoor, L. Advanced Methods for Knowledge Discovery from Complex Data (Maulik, U., Holder, L. & Cook, D.) (Springer-Verlag, 2005).
Getoor, L., Rhee, J., Koller, D. & Small, P. Understanding Tuberculosis Epidemiology Using Probabilistic Relational Models. AI in Medicine Journal 30, 233-256 (2004).
Getoor, L. Link Mining: A New Data Mining Challenge. SIGKDD Explorations, volume 5, 85- -89 (2003).
Getoor, L. Structure Discovery Using Statistical Relational Learning. Data Engineering Bulletin 26, 11- -18 (2003).
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. Learning Structured Statistical Models from Relational Data. Electronic Transactions on Artificial Intelligence 6, (2002).
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).
Getoor, L. Learning Statistical Models from Relational Data. (2001).PDF icon getoor-thesis.pdf (3.39 MB)
Getoor, L. Multi-relational Data Mining Using Probabilistic Models. Multi-Relational Data Mining Workshop (2001).PDF icon mrdm.pdf (109.57 KB)
Getoor, L., Segal, E., Taskar, B. & Koller, D. Probabilistic Models of Text and Link Structure for Hypertext Classification. IJCAI Workshop on Text Learning: Beyond Supervision (2001).PDF icon ijcai01-ws.pdf (127.03 KB)
Getoor, L., Koller, D. & Taskar, B. Selectivity estimation using probabilistic relational models. Proceedings of ACM-SIGMOD 2001 International Conference on Management of Data (2001).PDF icon sigmod01.pdf (471.72 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., 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. & Sahami, M. Using Probabilistic Relational Models for Collaborative Filtering. Working Notes of the KDD Workshop on Web Usage Analysis and User Profiling (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).
Getoor, L. & Fromherz, M. Online Scheduling for Reprographic Machines. Working notes AAAI Workshop on Online Search (1997).
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., Friedman, N., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. Relational Data Mining (Springer-Verlag, 2001).PDF icon lprm-ch.pdf (376 KB)
F
Friedman, N. & Getoor, L. Efficient Learning Using Constrained Sufficient Statistics. Uncertainty99 (1999).
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)
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)
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)
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)
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)
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)
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)
Fakhraei, S., Onukwugha, E. & Getoor, L. Healthcare Data Analytics (Reddy, C. C. Aggarwa) (CRC Press, 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)
Fakhraei, S., Huang, B. & Getoor, L. Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction. NIPS Workshop on Machine Learning in Computational Biology (MLCB) (2013).
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)
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)
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)
E
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)
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)
Embar, V., Pujara, J. & Getoor, L. Collective Alignment of Large-scale Ontologies. AKBC Workshop on Federated KBs and the Open Knowledge Network (2019).PDF icon embar-akbc19.pdf (47.25 KB)

Pages