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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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A

R. Arti, Jaebong, Y., Shitian, S., Getoor, L., and Jihie, K., “User Role Prediction in Online Discussion Forums using Probabilistic Soft Logic”, in NeuRIPS Workshop on PE, 2012.

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ramesh-pe11.pdf (40.65 KB)

E. Augustine and Getoor, L., “A Comparison of Bottom-Up Approaches to Grounding for Templated Markov Random Fields”, in Machine Learning and Systems (MLSys), 2018.

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augustine-sysml18.pdf (624.33 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)

E. Augustine, Rekatsinas, T., and Getoor, L., “Tractable Probabilistic Reasoning Through Effective Grounding”, in ICML Workshop on Tractable Probabilistic Modeling (TPM), 2019.

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augustine-tpm19.pdf (224.8 KB)

B

S. H. Bach, Huang, B., and Getoor, L., “Probabilistic Soft Logic for Social Good”, in KDD Workshop on Data Science for Social Good, 2014.

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bach-dssg14.pdf (124.88 KB)

S. H. Bach, Huang, B., London, B., and Getoor, L., “Hinge-loss Markov Random Fields: Convex Inference for Structured Prediction”, in Uncertainty in Artificial Intelligence, 2013.

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bach-uai13.pdf (379.45 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)

S. Bach, Broecheler, M., Getoor, L., and O'Leary, D., “Scaling MPE Inference for Constrained Continuous Markov Random Fields with Consensus Optimization”, in NeuRIPS, 2012.

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bach-nips12.pdf (274.58 KB)

S. H. Bach, Broecheler, M., Kok, S., and Getoor, L., “Decision-Driven Models with Probabilistic Soft Logic”, in NIPS Workshop on Predictive Models in Personalized Medicine, 2010.

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bach-pmpm10.pdf (246.79 KB)

S. H. Bach, Broecheler, M., Huang, B., and Getoor, L., “Hinge-Loss Markov Random Fields and Probabilistic Soft Logic”, Journal of Machine Learning Research (JMLR), vol. 18, pp. 1-67, 2017.

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bach-jmlr17.pdf (731.56 KB)

S. H. Bach, Broecheler, M., Huang, B., and Getoor, L., “Hinge-Loss Markov Random Fields and Probabilistic Soft Logic”, ArXiv:1505.04406 [cs.LG], 2015.

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bach-arxiv15.pdf (686.27 KB)

S. H. Bach, “Hinge-Loss Markov Random Fields and Probabilistic Soft Logic: A Scalable Approach to Structured Prediction”, University of Maryland, College Park, 2015.

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bach-thesis15.pdf (1.17 MB)

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)

S. H. Bach, Huang, B., and Getoor, L., “Unifying Local Consistency and MAX SAT Relaxations for Scalable Inference with Rounding Guarantees”, in Artificial Intelligence and Statistics (AISTATS), 2015.

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bach-aistats15.pdf (345.2 KB)

S. H. Bach, Huang, B., and Getoor, L., “Rounding Guarantees for Message-Passing MAP Inference with Logical Dependencies”, in NIPS Workshop on Discrete and Combinatorial Problems in Machine Learning (DISCML), 2014.

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bach-discml14.pdf (254.9 KB)

V. Barash, Smith, M., Getoor, L., and Welser, H., “Distinguishing Knowledge vs Social Capital in Social Media with Roles and Context”, in International Conference on Weblogs and Social Media, 2009.

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barash-icwsm09.pdf (171.16 KB)

H. Bert, Stephen, B., Eric, N., Jay, P., and Getoor, L., “Social Group Modeling with Probabilistic Soft Logic”, in NeuRIPS Workshop on SNSMA, 2012.

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huang-snsma12.pdf (1.02 MB)

I. Bhattacharya and Getoor, L., Collective Relational Clustering, 1st ed., vol. 1. Chapman and Hall, 2008, pp. 221-244.

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bhattacharya-book08.pdf (10.39 MB)

I. Bhattacharya and Getoor, L., “Collective Entity Resolution In Relational Data”, ACM Transactions on Knowledge Discovery from Data, vol. 1, pp. 1-36, 2007.

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bhattacharya-tkdd.pdf (346.13 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)

I. Bhattacharya and Getoor, L., “Query-time Entity Resolution”, Journal of Artificial Intelligence Research (JAIR), vol. 30, pp. 621–657, 2007.

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bhattacharya07a.pdf (309.63 KB)

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)

I. Bhattacharya, “Collective Entity Resolution In Relational Data”, University of Maryland, College Park, 2006.

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thesis.pdf (761.21 KB)

I. Bhattacharya and Getoor, L., “Collective Entity Resolution in Relational Data”, Data Engineering Bulletin, vol. 29, 2006.

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I. Bhattacharya and Getoor, L., “Entity Resolution in Social Networks”, in International Sunbelt Social Network Conference (Sunbelt XXVI), 2006.

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I. Bhattacharya and Getoor, L., Entity Resolutions in Graphs, 1st ed., vol. 1. Wiley, 2006, p. 311--344.

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bhattacharya-book06.pdf (482.5 KB)

I. Bhattacharya, Licamele, L., and Getoor, L., “Query-Time Entity Resolution”, in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2006.

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kdd06.pdf (183.45 KB)

I. Bhattacharya, Licamele, L., and Getoor, L., “Relational Clustering for Entity Resolution Queries”, in ICML Workshop on Statistical Relational Learning (SRL), 2006.

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bhattacharyaicml06-wkshp.pdf (195.79 KB)

I. Bhattacharya and Getoor, L., “Relational Clustering for Multi-type Entity Resolution”, in ACM SIGKDD Workshop on Multi Relational Data Mining (MRDM), 2005.

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bhattacharyakdd05-whskp.pdf (259.82 KB)

I. Bhattacharya and Getoor, L., “Deduplication and Group Detection using Links”, in ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD), 2004.

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bhattacharyakdd04-whskp.pdf (231.67 KB)

I. Bhattacharya and Getoor, L., “Iterative Record Linkage for Cleaning and Integration”, in ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD), 2004.

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bhattacharyasigmod04-wkshp.pdf (222.38 KB)

I. Bhattacharya, Getoor, L., and Bengio, Y., “Unsupervised Sense Disambiguation using Bilingual Probabilistic Models”, in Annual Meeting of the Association for Computational Linguistics (ACL), 2004.

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acl04.pdf (156.26 KB)

M. Bilgic and Getoor, L., “Value of Information Lattice: Exploiting Probabilistic Independence for Effective Feature Subset Acquisition”, Journal of Artificial Intelligence Research (JAIR), vol. 41, pp. 69–95, 2011.

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bilgic11a.pdf (1.64 MB)

M. Bilgic and Getoor, L., “Active Inference for Collective Classification”, in Twenty-Fourth Conference on Artificial Intelligence (AAAI NECTAR Track), 2010, pp. 1652–1655.

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bilgic-aaai10.pdf (387.53 KB)

M. Bilgic, Mihalkova, L., and Getoor, L., “Active Learning for Networked Data”, in Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010.

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bilgic-icml10.pdf (515.65 KB)

M. Bilgic, “Information Acquisition in Structured Domains”, University of Maryland - College Park, 2010.

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mbilgic-phdthesis.pdf (4.68 MB)

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)

M. Bilgic and Getoor, L., “Reflect and Correct: A Misclassification Prediction Approach to Active Inference”, ACM Transactions on Knowledge Discovery from Data, vol. 3, pp. 1–32, 2009.

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bilgic-tkdd09.pdf (3.66 MB)

M. Bilgic and Getoor, L., “Effective Label Acquisition for Collective Classification”, in ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008, pp. 43–51.

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bilgic-kdd08.pdf (758.14 KB)

M. Bilgic, Namata, G. Mark, and Getoor, L., “Combining Collective Classification and Link Prediction”, in Workshop on Mining Graphs and Complex Structures at the IEEE International Conference on Data Mining (ICDM-2007), 2007.

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mgcs07.pdf (105.13 KB)

M. Bilgic and Getoor, L., “VOILA: Efficient Feature-value Acquisition for Classification”, in AAAI '07: Proceedings of the 22nd National Conference on Artificial Intelligence, 2007.

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bilgic-aaai07.pdf (220.47 KB)

M. Bilgic, Licamele, L., Getoor, L., and Shneiderman, B., “D-Dupe: An Interactive Tool for Entity Resolution in Social Networks”, in Visual Analytics Science and Technology (VAST), Baltimore, 2006.

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M. Bilgic, Licamele, L., Getoor, L., and Shneiderman, B., “D-Dupe: An Interactive Tool for Entity Resolution in Social Networks”, in International Symposium on Graph Drawing, 2005, vol. 3843, pp. 505–507.

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ddupe.pdf (224.93 KB)

S. Bradley and Getoor, L., “Topic Modeling for Wikipedia Link Disambiguation”, ACM Transactions on Information Systems, vol. 32, 2014.

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M. Broecheler and Getoor, L., “Computing marginal distributions over continuous Markov networks for statistical relational learning”, in Advances in Neural Information Processing Systems (NIPS), 2010.

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broecheler-nips10.pdf (382.51 KB)

M. Broecheler, Mihalkova, L., and Getoor, L., “Probabilistic Similarity Logic”, in Conference on Uncertainty in Artificial Intelligence, 2010.

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broecheler-uai10.pdf (399.54 KB)

M. Broecheler and Getoor, L., “Probabilistic Similarity Logic”, in International Workshop on Statistical Relational Learning (SRL'09), 2009.

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broecheler-srl09.pdf (176.13 KB)

C

U. Chajewska, Norman, J., and Getoor, L., “Using Classication Techniques for Utility Elicitation: A Comparison between StandardGamble and Visual Analog Scale Methods”, in Twentieth Anniversary Meeting of the Society for Medical Decision Making, 1998.

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U. Chajewska, Getoor, L., Norman, J., and Shahar, Y., “Utility Elicitation as a Classication Problem”, in Uncertainty in Articial Intelligence, 1998.

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