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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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E. Zheleva, “Prediction, Evolution and Privacy in Social and Affiliation Networks”, University of Maryland College Park, 2011.

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zheleva-phdthesis11.pdf (5.81 MB)

L. Licamele and Getoor, L., “Predicting Protein-Protein Interactions Using Relational Features”, in ICML Workshop on Statistical Network Analysis, 2006.

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S. Tomkins, Ramesh, A., and Getoor, L., “Predicting Post-Test Performance from Online Student Behavior: A High School MOOC Case Study”, in EDM, 2016.

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tomkins-edm16.pdf (619.77 KB)

M. Rastegari, Choi, J., Fakhraei, S., III, H. Daume, and Davis, L., “Predictable Dual-View Hashing”, in Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013, pp. 1328–1336.

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rastegari13.pdf (2.35 MB)

A. Lansky and Getoor, L., “Practical Planning in COLLAGE”, in Proceedings of the AAAI Fall Symposium on Planning and Learning: On to Real Applications, 1994.

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P. Sen, Deshpande, A., and Getoor, L., “PrDB: Managing and Exploiting Rich Correlations in Probabilistic Databases”, VLDB Journal, special issue on uncertain and probabilistic databases, 2009.

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sen-vldbj09.pdf (1.12 MB)

G. Mark Namata and Getoor, L., “A Pipeline Approach to Graph Identification”, in Seventh International Workshop on Mining and Learning with Graphs, 2009.

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namatag-mlg09.pdf (93.77 KB)

P. Kouki, Schaffer, J., Pujara, J., Odonovan, J., and Getoor, L., “Personalized Explanations for Hybrid Recommender Systems”, in Intelligent User Interfaces (IUI), 2019.

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kouki-iui19.pdf (3.34 MB)

T. Elsayed, Oard, D., Namata, G. Mark, and Getoor, L., “Personal Name Resolution in Email: A Heuristic Approach”. University of Maryland, College Park, 2008.

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LAMP_150.pdf (397.61 KB)

S. H. Bach, Huang, B., Boyd-Graber, J., and Getoor, L., “Paired-Dual Learning for Fast Training of Latent Variable Hinge-Loss MRFs”, in International Conference on Machine Learning (ICML), 2015.

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bach-icml15.pdf (356.46 KB)

E. Hung, Getoor, L., and Subrahmanian, V. S., “PXML: A Probabilistic Semistructured Data Model and Algebra”, in Proceedings of the IEEE International Conference on Data Engineering, 2003.

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L. Getoor and Grant, J., “PRL: A Logical Approach to Probabilistic Relational Models”, Machine Learning Journal, vol. 62, 2006.

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getoor-mlj06.pdf (685.04 KB)

B. London, Huang, B., Taskar, B., and Getoor, L., “PAC-Bayesian Collective Stability”, in Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 2014.

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london-aistats14.pdf (490.14 KB)

B. London, Huang, B., Taskar, B., and Getoor, L., “PAC-Bayes Generalization Bounds for Randomized Structured Prediction”, in NIP Workshop on Perturbation, Optimization and Statistics, 2013.

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london-nips13ws.pdf (205.57 KB)

O

H. Hwang, Lauw, H., Getoor, L., and Ntoulas, A., “Organizing User Search Histories”, IEEE Transactions on Knowledge and Data Engineering, 2010.

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S. Somasundaran, Namata, G. Mark, Getoor, L., and Wiebe, J., “Opinion Graphs for Polarity and Discourse Classification”, in TextGraphs-4: Graph-based Methods for Natural Language Processing, 2009.

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somasundaran-textgraphs09.pdf (289.75 KB)

J. Pujara, Miao, H., Getoor, L., and Cohen, W., “Ontology-Aware Partitioning for Knowledge Graph Identification”, in CIKM Workshop on Automatic Knowledge Base Construction, 2013.

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pujara_akbc13.pdf (370.62 KB)

L. Getoor and Fromherz, M., “Online Scheduling for Reprographic Machines”, in Working notes AAAI Workshop on Online Search, 1997.

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J. Pujara, London, B., Getoor, L., and Cohen, W., “Online Inference for Knowledge Graph Construction.”, in Workshop on Statistical Relational AI, 2015.

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pujara-starai15.pdf (340.95 KB)

I. Bhattacharya and Getoor, L., “Online Collective Entity Resolution”, in The 22nd National Conference on Artificial Intelligence (NECTAR Track), 2007.

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nectar07.pdf (395.24 KB)

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S. Fakhraei, Huang, B., Raschid, L., and Getoor, L., “Network-Based Drug-Target Interaction Prediction with Probabilistic Soft Logic”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2014.

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fakhraei-tcbb2014_accepted.pdf (3.97 MB)

C. Diehl, Getoor, L., and Namata, G. Mark, “Name Reference Resolution in Organizational Email Archives”, in SIAM Conference on Data Mining (SDM), 2006.

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diehlsdm06.pdf (971.2 KB)

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A. Ramesh, Rodriguez, M., and Getoor, L., “Multi-relational influence models for online professional networks”, in International Conference on Web Intelligence (ICWI), 2017, pp. 291-298.

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ramesh-icwi17.pdf (761.17 KB)

B. London, Rekatsinas, T., Huang, B., and Getoor, L., “Multi-relational Weighted Tensor Decomposition”, in NIPS Workshop on SL, 2012.

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london-sl12.pdf (326.3 KB)

B. London, Rekatsinas, T., Huang, B., and Getoor, L., “Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss”. University of Maryland College Park, 2013.

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mrwtd.pdf (460.45 KB)

L. Getoor, “Multi-relational Data Mining Using Probabilistic Models”, in Multi-Relational Data Mining Workshop, 2001.

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mrdm.pdf (109.57 KB)

H. Sharara, Halgin, D., Getoor, L., and Borgatti, S., “Multi-dimensional Trajectory Analysis for Career Histories”, in International Sunbelt Social Networks Conference (Sunbelt XXXI), 2011.

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A. Ramesh, Goldwasser, D., Huang, B., III, H. Daume, and Getoor, L., “Modeling Learner Engagement in MOOCs using Probabilistic Soft Logic”, in NIPS Workshop on Data Driven Education, 2013.

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ramesh-nipsws13.pdf (153.92 KB)

B. Saha and Getoor, L., “On Maximum Coverage in the Streaming Model & Application to Multi-topic Blog-Watch”, in 2009 SIAM International Conference on Data Mining (SDM09), 2009.

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saha-sdm08.pdf (233.12 KB)

E. Augustine and Farnadi, G., “MLTrain: Collective Reasoning With Probabilistic Soft Logic”. Uncertainty in Artificial Intelligence (UAI), 2018.

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augustine-uai18.pdf (8.93 MB)

L

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)

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)

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)

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

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senum-tr07.pdf (511.11 KB)

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)

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)

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)

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

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

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

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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)

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)

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

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1107.4966v2.pdf (446.54 KB)

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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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)

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

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getoor-thesis.pdf (3.39 MB)

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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