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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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H. Sharara, Sopan, A., Namata, G. Mark, Getoor, L., and Singh, L., “G-PARE: A Visual Analytic Tool for Comparative Analysis of Uncertain Graphs”, in IEEE Conference on Visual Analytics Science and Technology (VAST), 2011.

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sharara-vast11.pdf (1.64 MB)

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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H. Sharara, Singh, L., Getoor, L., and Mann, J., “Understanding Actor Loyalty to Event-Based Groups in Affiliation Networks”, Journal of Advances in Social Networks Analysis and Mining, vol. 1, pp. 115–126, 2011.

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H. Sharara, Getoor, L., and Norton, M., “Active Surveying”, in NIPS Workshop on Networks Across Disciplines in Theory and Applications, 2010.

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H. Sharara, Norton, M., and Getoor, L., “Active Surveying for Leadership Identification”, in The International Sunbelt Social Networks Conference XXX, 2010.

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H. Sharara, Getoor, L., and Norton, M., “An Active Learning Approach for Identifying Key Opinion Leaders”, in The 2nd Workshop on Information in Networks (WIN), 2010.

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H. Sharara and Getoor, L., “Group Detection”, Encyclopedia of Machine Learning, 2010.

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H. Sharara, Singh, L., Getoor, L., and Mann, J., “The Dynamics of Actor Loyalty to Groups in Affiliation Networks”, in International Conference on Advances in Social Networks Analysis and Mining, 2009.

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sharara_asonam09.pdf (446.61 KB)

P. Sen, Namata, G. Mark, Bilgic, M., and Getoor, L., “Collective Classification”, Encyclopedia of Machine Learning, 2010.

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P. Sen, Deshpande, A., and Getoor, L., “Read-Once Functions and Query Evaluation in Probabilistic Databases”, in International Conference on Very Large Data Bases, 2010.

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draft.pdf (322 KB)

P. Sen, Deshpande, A., and Getoor, L., “Bisimulation-based Approximate Lifted Inference”, in Uncertainty in Artificial Intelligence, 2009.

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uai09.pdf (240.89 KB)

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)

P. Sen, “Representing and Querying Uncertain Data”, University of Maryland, College Park, 2009.

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thesis.pdf (1.12 MB)

P. Sen, Namata, G. Mark, Bilgic, M., Getoor, L., Gallagher, B., and Eliassi-Rad, T., “Collective Classification in Network Data”, AI Magazine, vol. 29, pp. 93–106, 2008.

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sen-aimag08.pdf (497.82 KB)

P. Sen and Getoor, L., “Cost-Sensitive Learning with Conditional Markov Networks”, Data Mining and Knowledge Discovery, Special Issue on Utility Based Data Mining, vol. 17, pp. 136–163, 2008.

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draft.pdf (424.09 KB)

P. Sen, Deshpande, A., and Getoor, L., “Exploiting Shared Correlations in Probabilistic Databases”, in International Conference on Very Large Data Bases, 2008.

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sen-vldb08.pdf (232.29 KB)

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

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senum-tr07.pdf (511.11 KB)

P. Sen and Deshpande, A., “Representing and Querying Correlated Tuples in Probabilistic Databases”, in International Conference on Data Engineering, 2007.

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icde07_final.pdf (309.63 KB)

P. Sen, Deshpande, A., and Getoor, L., “Representing Tuple and Attribute Uncertainty in Probabilistic Databases”, in Workshop on Data Mining of Uncertain Data (ICDM), 2007.

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dune07.pdf (176.67 KB)

P. Sen and Getoor, L., “Cost-Sensitive Learning with Conditional Markov Networks”, in SIAM Data Mining Workshop on Link Analysis, Counterterrorism and Security, 2006.

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sensiam_lacs06.pdf (137.37 KB)

P. Sen and Getoor, L., “Cost-Sensitive Learning with Conditional Markov Networks”, in International Conference on Machine Learning, 2006.

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senicml06.pdf (118.33 KB)

P. Sen and Getoor, L., “Empirical Comparison of Approximate Inference Algorithms for Networked Data”, in ICML Workshop on Statistical Relational Learning (SRL), 2006.

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sensrl06.pdf (225.32 KB)

V. Sehgal, Getoor, L., and Viechnicki, P., “Entity Resolution in Geospatial Data Integration”, in ACM GIS, 2006.

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K. Schnaitter, Polyzotis, N., and Getoor, L., “Index Interactions in Physical Design Tuning: Modeling, Analysis, and Applications”, in International Conference on Very Large Data Bases, 2009.

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schnaitter-vldb09.pdf (743.29 KB)

H. Sayyadi and Getoor, L., “Future Rank: Ranking Scientific Articles by Predicting their Future PageRank”, in 2009 SIAM International Conference on Data Mining (SDM09), 2009.

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sayyadi_futureRank_sdm09.pdf (621.55 KB)

B. Salami, Parikh, H., Kayali, M., Roy, S., Getoor, L., and Suciu, D., “Causal Relational Learning”, in International Conference on Management of Data (SIGMOD), 2020.

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salami-sigmod20.pdf (1.02 MB)

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)

B. Saha and Getoor, L., “Group Proximity Measure for Recommending Groups in Online Social Networks”, in 2nd ACM SIGKDD Workshop on Social Network Mining and Analysis (SNA-KDD), 2008.

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kddw-saha.pdf (311.36 KB)

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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)

T. Rekatsinas, Dong, X. Luna, Getoor, L., and Srivastava, D., “Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration”, in 7th Biennial Conference on Innovative Data Systems Research (CIDR `15), 2015.

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rekatsinasCIDR15.pdf (396.99 KB)

T. Rekatsinas, “Quality-Aware Data Source Management”, University of Maryland, College Park, 2015.

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T. Rekatsinas, Ghosh, S., Mekaru, S., Nsoesie, E., Brownstein, J., Getoor, L., and Ramakrishnan, N., “SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources”, in 2015 SIAM International Conference on Data Mining (SDM15), 2015.

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rekatsinasSDM2015.pdf (303.08 KB)

T. Rekatsinas, Deshpande, A., Dong, L., Getoor, L., and Srivastava, D., “SourceSight: Enabling Effective Source Selection”, in SIGMOD, 2016.

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rekatsinas-sigmod16.pdf (799.94 KB)

T. Rekatsinas, Ghosh, S., Mekaru, S., Nsoesie, E., Brownstein, J., Getoor, L., and Ramakrishnan, N., “Forecasting Rare Disease Outbreaks Using Multiple Data Sources”, STAT ANAL DATA MIN, 2015.

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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. 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. Ramesh, Goldwasser, D., Huang, B., III, H. Daume, and Getoor, L., “Uncovering Hidden Engagement Patterns for Predicting Learner Performance in MOOCs”, in ACM Conference on Learning at Scale, 2014.

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A. Ramesh, Goldwasser, D., Huang, B., Daume, III, H., and Getoor, L., “Understanding MOOC Discussion Forums using Seeded LDA”, in ACL Workshop on Innovative Use of NLP for Building Educational Applications, 2014.

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ramesh-aclws14.pdf (137.57 KB)

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)

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)

A. Ramesh, Rodriguez, M., and Getoor, L., “Understanding Influence in Online Professional Networks”, in NIPS Workshop on Networks in Social and Information Sciences, 2015.

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ramesh-nipsws15.pdf (211.44 KB)

A. Ramesh, Kumar, S., Foulds, J., and Getoor, L., “Weakly Supervised Models of Aspect-Sentiment for Online Course Discussion Forums”, in 53rd Annual Meeting of the Association for Computational Linguistics (ACL), 2015.

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ramesh-acl15.pdf (168.7 KB)

A. Ramesh, “A Probabilistic Approach to Modeling Socio-Behavioral Interactions”, University of Maryland, College Park, 2016.

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ramesh-thesis16.pdf (865.41 KB)

A. Ramesh and Getoor, L., “Understanding Evolution of Long-running MOOCs”, in International Conference on Web Information Systems Engineering (WISE), 2018.

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A. Ramesh, Goldwasser, D., Huang, B., Daume, III, H., and Getoor, L., “Interpretable Engagement Models for MOOCs using Hinge-loss Markov Random Fields”, IEEE Transactions on Learning Technologies (TLT), vol. 14, pp. 1-1, 2019.

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ramesh-tlt19.pdf (4.3 MB)

N. Ramakrishnan, Butler, P., Self, N., Khandpur, R., Saraf, P., Wang, W., Cadena, J., Vullikanti, A., Korkmaz, G., Kuhlman, C., Marathe, A., Zhao, L., Ting, H., Huang, B., Srinivasan, A., Trinh, K., Getoor, L., Katz, G., Doyle, A., Ackermann, C., Zavorin, I., Ford, J., Summers, K., Fayed, Y., Arredondo, J., Gupta, D., and Mares, D., “‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators”, in ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2014.

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ramakrishnan-kdd14.pdf (1.15 MB)

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J. Pujara, Miao, H., and Getoor, L., “Joint Judgments with a Budget: Strategies for Reducing the Cost of Inference”, in ICML Workshop on Machine Learning with Test-Time Budgets, 2013.

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pujara_wtbudg13.pdf (221.26 KB)

J. Pujara, Miao, H., Getoor, L., and Cohen, W., “Knowledge Graph Identification”, in International Semantic Web Conference (ISWC), 2013.

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pujara_iswc13.pdf (508.7 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)

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