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Author anyAckermann, Chris Aggarwal, Charu Amantullah, Brian Ariel, Fuxman Arredondo, Jaime Arredondo, Jaime Arti, Ramesh Augustine, Eriq Babaki, Behrouz Bach, Stephen H.Bach, Stephen Barash, Vladimir Beard, Mitchell Bengio, Yoshua Bert, Huang Bhattacharya, Indrajit Bhattacharya, Indrajit Bilgic, Mustafa Bilgic, Mustafa Blake, Brian Blondeel, Marjon Borgatti, Steve Boyd-Graber, Jordan Bradley, Skaggs Broecheler, Matthias Broecheler, Matthias Brownstein, John Brownstein, John Butler, Patrick Cadena, Jose Carlson, Bjorn Carstea, Eugene Chajewska, Ursulza Chang, Johnnie Chen, Daozheng Chen, Yunfei Chen, Robert Choi, Jonghyun Cohen, William Cook, Diane Daozheng, Chen Daume, Hal David, Jacobs Davis, Larry Davis, Larry De Cock, Martine Deshpande, Amol Deshpande, Amol Dhanya, Sridhar Diehl, Christopher Dietterich, Thomas Djeraba, Chabane Domingos, Pedro Dong, Xin LunaDong, Luna Dong, Xin LunaDoppa, Janardhan Doyle, Andy Dzeroski, Saso Eirinaki, Magdalini Eliassi-Rad, Tina Elsayed, Tamer Embar, Varun Eric, Norris Fakhraei, Shobeir Fakhraei, Shobeir Faloutsos, Christos Farnadi, Golnoosh Fayed, Youssef Feldman, Ronen Ford, Jim Foulds, James Foulds, James Friedman, Nir Friedman, Nir Friedman, Mark Fromherz, Markus Gallagher, Brian Gazen, Bora C.Getoor, Lise Ghosh, Saurav Ghosh, Saurav Golbeck, Jennifer Golbeck, Jennifer Goldwasser, Dan Goldwasser, Dan Grant, John Grossman, Robert Grycner, Adam Grycner, Adam Guiver, John Gupta, Dipak Gupta, Dipak Haidarian-Shahri, Hamid Halgin, Daniel Han, Jiawei He, Xinran Healy, Patrick Holder, Lawrence Hollis, Victoria Hossam, Sharara Huang, Bert Huang, Bert Hung, Edward Hwang, Heasoo III, Hal DaumeIslamaj, Rezarta Islamaj, Rezarta Isley, Steve Jacobs, David Jaebong, Yoo Janet, Mann Jay, Pujara Jihie, Kim Jr., Nick ShortKang, Jeonhyung Kang, Hyunmo Katz, Graham Katz, Graham Kayali, Moe Khamis, Sameh Khandpur, Rupinder Kim, Sungchul Kimmig, Angelika Kimmig, Angelika Kini, Nikhil Knoblock, Craig Koehly, Laura Koehly, Laura Koh, Eunyee Kok, Stanley Kolcz, Alek Koller, Daphne Koller, Daphne Korkmaz, Gizem Kouki, Pigi Kouki, Pigi Kuhlman, Christopher Kumar, Shachi Kumar, Shachi Kuter, Ugur Lansky, Amy Lauw, Hady Lavedan, Christian Lavrac, Nada Lerman, Kristina Licamele, Louis Lilyana, Mihalkova Lisa, Singh Liu, Xiangyang Liu, Huan Liu, Yan London, Ben London, Ben Lu, Qing Machanavajjhala, Ashwin Machanavajjhala, Ashwin Mack, Kendra Macskassy, Sofus Mann, Janet Marathe, Achla Marcum, Christopher Marcum, Christopher Mares, David Mares, David Maulik, Ujjwal Mekaru, Sumiko Mekaru, Sumiko Memory, Alex Memory, Alex Miao, Hui Miao, Hui Michelson, Matthew Mihalkova, Lilyana Milic-Frayling, Natasa Miller, Renee Miller, Renee JMinton, Steve Minton, Steven Mitkus, Shruti Moens, Marie-Francine Motoda, Hiroshi Mount, Stephen Moustafa, Walaa EldinMoustafa, Walaa Moustafa, Walaa Muggleton, Stephen Mustafa, Bilgic Muthiah, Sathappan Myra, Norton Namata, Galileo MarkNamata, Galileo Namata, Galileo Navlakha, Saket Nikolov, Nikola S.Norman, Joseph Norton, Myra Nsoesie, Elaine Nsoesie, Elaine Ntoulas, Alexcandros O'Donovan, John O'Leary, Dianne ODonovan, John Oard, Doug Odonovan, John Onukwugha, Eberechukwu Ottosson, Gregor Panagiotis, Papadimitriou Panayiotis, Tsaparas Parikh, Harsh Pfeffer, Avi Pfeffer, Avi Piatetsky-Shapiro, Gregory Plangprasopchok, Anon Polymeropoulos, Mihales Polyzotis, Neoklis Pujara, Jay Pujara, Jay Ramakrishnan, Naren Ramakrishnan, Naren Ramesh, Arti Ramesh, Arti Rand, William Rao, Nikhil SRaschid, Louiqa Raschid, Louiqa Rastegari, Mohammad Rathod, Priyang Rekatsinas, Theodoros Rekatsinas, Theodoros Rhee, Jeanne Riloff, Ellen Rodrigues, Eduarda MendesRodriguez, Mario Roussopoulos, Nick Roy, Sudeepa Saha, Barna Sahami, Mehran Salami, Babak Saraf, Parang Sarawagi, Sunita Sayyadi, Hassan Schaffer, James Schaffer, James Scheffer, Tobias Schmidler, Scott Schnaitter, Karl See, Kane Segal, Eran Sehgal, Vivek Self, Nathan Sen, Prithviraj Sen, Prithviraj Shahar, Yuval Sharara, Hossam Sharara, Hossam Shashanka, Madhusudana Shitian, Shen Shneiderman, Ben Singh, Lisa Sisman, Bunyamin Skomoroch, Peter Small, Peter Smith, Marc Somasundaran, Swapna Sopan, Awalin Springer, Aaron Sridhar, Dhanya Srinivasan, Aravind Srinivasan, Sriram Srivastava, Ashok Srivastava, Divesh Srivastava, Divesh Staats, Brian Stephen, Bach Subbaian, Karthik Subrahmanian, V. S.Suciu, Dan Summers, Kristin Tadepalli, Prasad Taskar, Benjamin Terzi, Evimaria Thompson, Spencer K.Ting, Hua Tom, Yeh Tomkins, Sabina Tomkins, Sabina Trinh, Khoa Udrea, Octavian Viechnicki, Peter Volpi, Simona Vullikanti, Anil Walker, Marilyn Wang, Wei Wei, Hao Weikum, Gerhard Weikum, Gerhard Welser, Howard Whittaker, Steve Wiebe, Janyce Wilbur, John Wilbur, John Yu, Philip Yu, Jun Zaki, Mohammed Zavorin, Ilya Zhang, Yi Zhang, Yue Zhao, Liang Zhao, Bin Zheleva, Elena Zheleva, Elena desJardins, Marie

Type anyConference PaperJournal ArticleThesisTutorialBookUnpublished

Term any

Year any20202019201820172016201520142013201220112010200920082007200620052004200320022001200019991998199719951994

Keyword anyCognitionComparative AnalysisComplexity theoryData engineeringDiscussion ForumsFirst-order probabilistic modelsHL-MRFsKnowledge engineeringLDALifted inference and learningMOOCMOOC Discussion ForumsMOOCsMetadataModel ComparisonOnline CoursesPAC-BayesPar-factor graphsProbabilistic logicProbabilistic programmingSRLSchema mappingSeeded LDASocio-behavioral modelsStatistical relational learningTask analysisTemplated graphical modelsUncertain GraphsVisualizing Uncertaintyanonymity onlinebioinformatics gene expression analysis antipsychotic pharmacogeneticscollective classificationcollective mapping discoverydata integrationdefectfeature generationfunctional biological signalsgene expression bioinformatics drug therapeuticsgeneralization boundsgroupshigh school MOOCsinference mechanismsinfluencelatent variable modelslearner engagementlearning analyticslearning theorymeta dataonline educationoptimisationoptimizationpotential mappingsprivacyprobabilistic modelingprobabilistic reasoning techniquesprobabilistic soft logicprobabilityprofessional networksschema mapping optimization problemsearchsensitive attribute inferencesocial mediasocial networkssplice-sitestatistical relational languagestructured predictionstudent learningtutorialuncertainty handlingweb

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2019

S. Srinivasan, Babaki, B., Farnadi, G., and Getoor, L., “Lifted Hinge-Loss Markov Random Fields”, in AAAI Conference on Artificial Intelligence (AAAI), 2019.

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srinivasan-aaai19.pdf (417.5 KB)

2015

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

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Foulds2015LatentTopicNetworks.pdf (382.53 KB)

A. Kimmig, Mihalkova, L., and Getoor, L., “Lifted graphical models: a survey”, Machine Learning Journal, vol. 99, pp. 1–45, 2015.

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kimmig-mlj15.pdf (785.58 KB)

2014

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

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ramesh-aaai14.pdf (505.47 KB)

A. Kimmig, Mihalkova, L., and Getoor, L., “Lifted graphical models: a survey”, Machine Learning, pp. 1-45, 2014.

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2013

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

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kang-sbp13.pdf (622.52 KB)

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

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pujara_slg13.pdf (277.63 KB)

J. Pujara, Miao, H., Getoor, L., and Cohen, W., “Large-Scale Knowledge Graph Identification using PSL”, in AAAI Fall Symposium on Semantics for Big Data, 2013.

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pujara_s4bd13.pdf (306.96 KB)

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

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bach-fna13.pdf (210.09 KB)

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

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bach-inferning13.pdf (348.79 KB)

2012

J. Pujara and Skomoroch, P., “Large-Scale Hierarchical Topic Models”, in NIPS Workshop on BigLearn, 2012.

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pujara_biglearn12.pdf (189.96 KB)

T. Rekatsinas, Deshpande, A., and Getoor, L., “Local Structure and Determinism in Probabilistic Databases”, in SIGMOD, 2012.

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rekatsinas-sigmod12.pdf (490.28 KB)

2011

L. Mihalkova, Moustafa, W. Eldin, and Getoor, L., “Learning to Predict Web Collaborations”, in WSDM Workshop on User Modeling for Web Applications, 2011.

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mihalkova-wikiCollabs.pdf (353.9 KB)

L. Mihalkova and Getoor, L., “Lifted Graphical Models: A Survey”. 2011.

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1107.4966v2.pdf (446.54 KB)

2010

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

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doppa-ecml10.pdf (203 KB)

G. Mark Namata and Getoor, L., “Link Prediction”, Encyclopedia of Machine Learning, 2010.

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2009

M. Bilgic and Getoor, L., “Link-based Active Learning”, in NIPS Workshop on Analyzing Networks and Learning with Graphs, 2009.

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mbilgic-nips09wkshp.pdf (116.35 KB)

2008

M. Smith, Barash, V., Getoor, L., and Lauw, H., “Leveraging Social Context for Searching Social Media”, in CIKM Workshop on Search in Social Media, 2008.

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2007

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

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p449.pdf (509.48 KB)

P. Sen and Getoor, L., “Link-based Classification”. University of Maryland, 2007.

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senum-tr07.pdf (511.11 KB)

2006

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

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bhattacharyasdm06.pdf (209.24 KB)

2005

L. Getoor and Diehl, C., “Link Mining: A Survey”, SigKDD Explorations Special Issue on Link Mining, vol. 7, 2005.

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L. Getoor, Link-based Classification, 1st ed., vol. 1. Springer-Verlag, 2005, p. 189--207.

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getoor-book05.pdf (273.43 KB)

2003

L. Getoor, “Link Mining: A New Data Mining Challenge”, SIGKDD Explorations, volume, vol. 5, p. 85- -89, 2003.

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

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lu-icml03.pdf (195.81 KB)

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

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icml03-ws.pdf (274.65 KB)

Q. Lu and Getoor, L., “Link-based Text Classification”, in IJCAI Workshop on "Text Mining and Link Analysis", 2003.

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ijcai03-ws.pdf (97.25 KB)

2002

L. Getoor, Friedman, N., Koller, D., and Taskar, B., “Learning Probabilistic Models of Link Structure”, Journal of Machine Learning Research, vol. 3, p. 679- -707, 2002.

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jmlr02.pdf (502.22 KB)

L. Getoor, Friedman, N., and Koller, D., “Learning Structured Statistical Models from Relational Data”, Electronic Transactions on Artificial Intelligence, vol. 6, 2002.

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2001

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

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icml01.pdf (157.91 KB)

L. Getoor, Friedman, N., Koller, D., and Pfeffer, A., Learning Probabilistic Relational Models, 1st ed., vol. 1. Springer-Verlag, 2001, p. 307--335.

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L. Getoor, Friedman, N., Koller, D., and Pfeffer, A., “Learning Probabilistic Relational Models”, in Relational Data Mining, 2001.

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lprm-ch.pdf (376 KB)

L. Getoor, “Learning Statistical Models from Relational Data”, Stanford, 2001.

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getoor-thesis.pdf (3.39 MB)

2000

L. Getoor, Koller, D., Taskar, B., and Friedman, N., “Learning Probabilistic Relational Models with Structural Uncertainty”, in Proceedings of the AAAI Workshop on Learning Statistical Models from Relational Data, 2000.

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1999

N. Friedman, Getoor, L., Koller, D., and Pfeffer, A., “Learning Probabilistic Relational Models”, in International Joint Conference on Articial Intelligence, 1999.

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icjai99.pdf (156.94 KB)

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