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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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D

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. Fakhraei, Onukwugha, E., and Getoor, L., Data Analytics for Pharmaceutical Discoveries, 1st ed., vol. 1. CRC Press, 2015, p. 1--25.

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fakhraei-book15.pdf (234.2 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)

C

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 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)

V. Embar, Sisman, B., Wei, H., Dong, X. Luna, Faloutsos, C., and Getoor, L., “Contrastive Entity Linkage: Mining Variational Attributes from Large Catalogs for Entity Linkage”, in Automated Knowledge Base Construction (AKBC), 2020.

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embar-akbc20.pdf (499.49 KB)

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. Polymeropoulos, Licamele, L., Volpi, S., Mack, K., Mitkus, S., Carstea, E., Getoor, L., and Lavedan, C., “Common effect of antipsychotics on the biosynthesis and regulation of fatty acids and cholesterol supports a key role of lipid homeostasis in schizophrenia.”, Schizophrenia Research, 2009.

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O. Udrea and Getoor, L., “Combining statistical and logical inference for ontology alignment”, in Workshop on Semantic Web for Collaborative Knowledge Acquisition at the International Joint Conference on Artificial Intelligence, 2007.

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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)

D. Sridhar, Foulds, J., Huang, B., Walker, M., and Getoor, L., “Collective classification of stance and disagreement in online debate forums”, in Bay Area Machine Learning Symposium (BayLearn), 2014.

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D. Sridhar, Getoor, L., and Walker, M., “Collective Stance Classification of Posts in Online Debate Forums”, in ACL Joint Workshop on Social Dynamics and Personal Attributes in Social Media, 2014.

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sridhar-aclws14.pdf (190.8 KB)

B. London, Huang, B., Taskar, B., and Getoor, L., “Collective Stability in Structured Prediction: Generalization from One Example”, in ICML, 2013.

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london-icml13.pdf (373.82 KB)

S. Fakhraei, Foulds, J., Shashanka, M., and Getoor, L., “Collective Spammer Detection in Evolving Multi-Relational Social Networks”, in KDD, 2015.

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fakhraei-kdd2015.pdf (573.89 KB)

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)

A. Kimmig, Memory, A., Miller, R., and Getoor, L., “A Collective, Probabilistic Approach to Schema Mapping”, in International Conference on Data Engineering (ICDE), 2017.

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kimmig-icde17.pdf (463.69 KB)

S. Fakhraei, Huang, B., and Getoor, L., “Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction”, in NIPS Workshop on MLCB, 2013.

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fakhraei-mlcb13.pdf (243.86 KB)

G. Namata, Kok, S., and Getoor, L., “Collective Graph Identification”, in KDD, 2011.

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namata-kdd11.pdf (185.7 KB)

G. Namata, London, B., and Getoor, L., “Collective Graph Identification”, TKDD, vol. 10, 2015.

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namata-tkdd15.pdf (500.96 KB)

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

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P. Kouki, Pujara, J., Marcum, C., Koehly, L., and Getoor, L., “Collective Entity Resolution in Multi-Relational Familial Networks”, Knowledge and Information Systems (KAIS), vol. 61, no. 3, p. 1547-–1581, 2018.

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kouki-kais18.pdf (1.17 MB)

P. Kouki, Pujara, J., Marcum, C., Koehly, L., and Getoor, L., “Collective Entity Resolution in Familial Networks”, in IEEE International Conference on Data Mining (ICDM), 2017.

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kouki-icdm17.pdf (653.4 KB)

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

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thesis.pdf (761.21 KB)

B. London and Getoor, L., Collective Classification of Network Data, 1st ed., vol. 1. CRC Press, 2013, p. 399--416.

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london-book13.pdf (394.37 KB)

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)

G. Namata, Sen, P., Bilgic, M., and Getoor, L., Collective Classification for Text Classification, 1st ed., vol. 1. Taylor and Francis Group, 2009, p. 51--69.

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namata-book09.pdf (4.35 MB)

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

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V. Embar, Pujara, J., and Getoor, L., “Collective Alignment of Large-scale Ontologies”, in AKBC Workshop on Federated Knowledge Bases (FKBs), 2019.

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embar-fkbs19.pdf (57.36 KB)

B. London, Khamis, S., Bach, S., Huang, B., Getoor, L., and Davis, L., “Collective Activity Detection using Hinge-loss Markov Random Fields”, in CVPR Workshop on SPTLE, 2013.

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london-sptle13.pdf (705.87 KB)

A. Lansky, Friedman, M., Getoor, L., Schmidler, S., and Jr., N. Short, “The Collage/Khoros Link: Planning for Image Processing Tasks”, in Proceedings of the AAAI Spring Symposium on Integrated Planning Applications, 1995.

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E. Zheleva, Sharara, H., and Getoor, L., “Co-evolution of Social and Affiliation Networks”, in 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2009.

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fp659-zheleva.pdf (900 KB)

J. Pujara and Getoor, L., “Coarse-to-Fine, Cost-Sensitive Classification of E-Mail”, in NIPS Workshop on Coarse-to-Fine Processing, 2010.

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pujara_nips10.pdf (258.86 KB)

J. Chang, Chen, R., Pujara, J., and Getoor, L., “Clustering System Data using Aggregate Measures”, in Machine Learning and Systems (MLSys), 2018.

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chang-sysml18.pdf (299.32 KB)

R. Islamaj, Getoor, L., and W. Wilbur, J., “Characterizing RNA secondary-structure features and their effects on splice-site prediction”, in IEEE ICDM Workshop on Mining and Management of Biological Data, 2007.

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J. Doppa, Yu, J., Tadepalli, P., and Getoor, L., “Chance-Constrained Programs for Link Prediction”, in NIPS Workshop on Analyzing Networks and Learning with Graphs, 2009.

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doppa-nips09wkshp.pdf (161.38 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)

S. Muthiah, Huang, B., Arredondo, J., Mares, D., Getoor, L., Katz, G., and Ramakrishnan, N., “Capturing Planned Protests from Open Source Indicators”, AI Mag, vol. 37, pp. 63–75, 2016.

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muthiah-aimag16.pdf (1.23 MB)

L. Licamele, Bilgic, M., Getoor, L., and Roussopoulos, N., “Capital and Benefit in Social Networks”, in ACM SIGKDD Workshop on Link Analysis and Group Detection (LinkKDD), 2005.

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licamele_linkkdd05.pdf (421.14 KB)

H. Kang, Getoor, L., and Singh, L., “C-GROUP: A Visual Analytic Tool for Pairwise Analysis of Dynamic Group Membership”, in Visual Analytics Science and Technology (VAST), 2007.

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vast07-kang.pdf (663.26 KB)

B

J. Pujara and Getoor, L., “Building Dynamic Knowledge Graphs”, in NIPS Workshop on Automated Knowledge Base Construction, 2014.

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pujara_akbc14.pdf (143.26 KB)

J. Pujara, London, B., and Getoor, L., “Budgeted Online Collective Inference”, in UAI, 2015.

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pujara-uai15.pdf (302.63 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)

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)

M. desJardins, Rathod, P., and Getoor, L., “Bayesian Network Learning with Abstraction Hierarchies and Context-Specific Independence”, in 16th European Conference on Machine Learning (ECML), 2005.

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S. Srinivasan, Farnadi, G., and Getoor, L., “BOWL: Bayesian Optimization for Weight Learning in Probabilistic Soft Logic”, in AAAI Conference on Artificial Intelligence (AAAI), 2020.

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srinivasan-aaai20a.pdf (478.65 KB)

A

V. Embar, Farnadi, G., Pujara, J., and Getoor, L., “Aligning Product Categories using Anchor Products”, in Workshop on Knowledge Base Construction, Reasoning and Mining (KBCOM), 2018.

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embar-kbcom18.pdf (577.65 KB)

S. Fakhraei, Dhanya, S., Pujara, J., and Getoor, L., “Adaptive Neighborhood Graph Construction for Inference in Multi-Relational Networks”, in KDD, 2016.

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