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2019

Srinivasan, S., Babaki, B., Farnadi, G. & Getoor, L. Lifted Hinge-Loss Markov Random Fields. 33rd AAAI Conference on Artificial Intelligence (2019).

srinivasan-aaai19.pdf (417.5 KB)

2015

Foulds, J., Kumar, S. & Getoor, L. Latent Topic Networks: A Versatile Probabilistic Programming Framework for Topic Models. International Conference on Machine Learning (ICML) (2015).

Foulds2015LatentTopicNetworks.pdf (382.53 KB)

Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning Journal 99, 1–45 (2015).

kimmig-mlj15.pdf (785.58 KB)

2014

Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Learning Latent Engagement Patterns of Students in Online Courses. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI Press, 2014).

ramesh-aaai14.pdf (505.47 KB)

Kimmig, A., Mihalkova, L. & Getoor, L. Lifted graphical models: a survey. Machine Learning 1-45 (2014).

2013

Kang, J., Lerman, K. & Getoor, L. LA-LDA: A Limited Attention Topic Model for Social Recommendation. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).

kang-sbp13.pdf (622.52 KB)

Pujara, J., Miao, H., Getoor, L. & Cohen, W. Large-Scale Knowledge Graph Identification using PSL. ICML Workshop on Structured Learning (SLG) (2013).

pujara_slg13.pdf (277.63 KB)

Pujara, J., Miao, H., Getoor, L. & Cohen, W. Large-Scale Knowledge Graph Identification using PSL. AAAI Fall Symposium on Semantics for Big Data (2013).

pujara_s4bd13.pdf (306.96 KB)

Bach, S. H., Huang, B. & Getoor, L. Large-margin Structured Learning for Link Ranking. NIPS Workshop on Frontiers of Network Analysis: Methods, Models, and Applications (2013).

bach-fna13.pdf (210.09 KB)

Bach, S. H., Huang, B. & Getoor, L. Learning Latent Groups with Hinge-loss Markov Random Fields. ICML Workshop on Inferning: Interactions between Inference and Learning (2013).

bach-inferning13.pdf (348.79 KB)

2012

Pujara, J. & Skomoroch, P. Large-Scale Hierarchical Topic Models. NIPS Workshop on Big Learning (2012).

pujara_biglearn12.pdf (189.96 KB)

Rekatsinas, T., Deshpande, A. & Getoor, L. Local Structure and Determinism in Probabilistic Databases. ACM SIGMOD Conference (2012).

sigmod_AAC2012.pdf (490.28 KB)

2011

Mihalkova, L., Moustafa, W. Eldin & Getoor, L. Learning to Predict Web Collaborations. WSDM Workshop on User Modeling for Web Applications (2011).

mihalkova-wikiCollabs.pdf (353.9 KB)

Mihalkova, L. & Getoor, L. Lifted Graphical Models: A Survey. (2011).

1107.4966v2.pdf (446.54 KB)

2010

Doppa, J., Yu, J., Tadepalli, P. & Getoor, L. Learning Algorithms for Link Prediction based on Chance Constraints. European Conference on Machine Learning (ECML) (2010).

doppa-ecml10.pdf (203 KB)

Namata, G. Mark & Getoor, L. Link Prediction. Encyclopedia of Machine Learning (2010).

2009

Bilgic, M. & Getoor, L. Link-based Active Learning. NIPS Workshop on Analyzing Networks and Learning with Graphs (2009).

mbilgic-nips09wkshp.pdf (116.35 KB)

2008

Smith, M., Barash, V., Getoor, L. & Lauw, H. Leveraging Social Context for Searching Social Media. CIKM Workshop on Search in Social Media (2008).

2007

Udrea, O., Getoor, L. & Miller, R. Leveraging Data and Structure in Ontology Integration. Proceedings of ACM-SIGMOD 2007 International Conference on Management 449–460 (2007).

p449.pdf (509.48 KB)

Sen, P. & Getoor, L. Link-based Classification. (2007).

senum-tr07.pdf (511.11 KB)

2006

Bhattacharya, I. & Getoor, L. A Latent Dirichlet Model for Unsupervised Entity Resolution. SIAM Conference on Data Mining (SDM) (2006).

bhattacharyasdm06.pdf (209.24 KB)

2005

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).

2003

Getoor, L. Link Mining: A New Data Mining Challenge. SIGKDD Explorations, volume 5, 85- -89 (2003).

Lu, Q. & Getoor, L. Link-based Classification. Proceedings of the International Conference on Machine Learning (ICML) (2003).

lu-icml03.pdf (195.81 KB)

Lu, Q. & Getoor, L. Link-based Classification Using Labeled and Unlabeled Data. ICML Workshop on "The Continuum from Labeled to Unlabeled Data in Machine Learning and Data Mining (2003).

icml03-ws.pdf (274.65 KB)

Lu, Q. & Getoor, L. Link-based Text Classification. IJCAI Workshop on "Text Mining and Link Analysis" (2003).

ijcai03-ws.pdf (97.25 KB)

2002

Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Link Structure. Journal of Machine Learning Research 3, 679- -707 (2002).

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).

2001

Getoor, L., Friedman, N., Koller, D. & Taskar, B. Learning Probabilistic Models of Relational Structure. Proceedings of International Conference on Machine Learning (ICML) (2001).

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., Friedman, N., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. Relational Data Mining (Springer-Verlag, 2001).

lprm-ch.pdf (376 KB)

Getoor, L. Learning Statistical Models from Relational Data. (2001).

getoor-thesis.pdf (3.39 MB)

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).

1999

Friedman, N., Getoor, L., Koller, D. & Pfeffer, A. Learning Probabilistic Relational Models. International Joint Conference on Articial Intelligence (1999).

icjai99.pdf (156.94 KB)