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

Type anyConference PaperJournal ArticleThesisTutorialBook ChapterUnpublishedPosterBook

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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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2012

London, B., Huang, B. & Getoor, L. Improved Generalization Bounds for Large-scale Structured Prediction. NIPS Workshop on Algorithmic and Statistical Approaches for Large Social Networks (2012).

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london-nips12ws.pdf (213.95 KB)

London, B., Rekatsinas, T., Huang, B. & Getoor, L. Multi-relational Weighted Tensor Decomposition. NIPS Workshop on Spectral Learning (2012).

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london-nips12ws-mrwtd.pdf (326.3 KB)

Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. Probabilistic Soft Logic for Trust Analysis in Social Networks. International Workshop on Statistical Relational Artificial Intelligence (StaRAI 2012) (2012).

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huang-starai12.pdf (241.96 KB)

Namata, G. Mark, London, B., Getoor, L. & Huang, B. Query-driven Active Surveying for Collective Classification. Workshop on Mining and Learning with Graphs (2012).

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namata-mlg12.pdf (257.49 KB)

Kimmig, A., Bach, S. H., Broecheler, M., Huang, B. & Getoor, L. A Short Introduction to Probabilistic Soft Logic. NIPS Workshop on Probabilistic Programming: Foundations and Applications (2012).

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psl_pp12.pdf (164.6 KB)

Huang, B., Bach, S. H., Norris, E., Pujara, J. & Getoor, L. Social Group Modeling with Probabilistic Soft Logic. NIPS 2012 Workshop - Social Network and Social Media Analysis: Methods, Models, and Applications (2012).

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2013

London, B. et al. Collective Activity Detection using Hinge-loss Markov Random Fields. CVPR Workshop on Structured Prediction: Tractability, Learning and Inference (2013).

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london-cvpr13.pdf (705.87 KB)

Fakhraei, S., Huang, B. & Getoor, L. Collective Inference and Multi-Relational Learning for Drug–Target Interaction Prediction. NIPS Workshop on Machine Learning in Computational Biology (MLCB) (2013).

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London, B., Huang, B., Taskar, B. & Getoor, L. Collective Stability in Structured Prediction: Generalization from One Example. Proceedings of the 30th International Conference on Machine Learning (ICML-13) (2013).

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london-icml13-long.pdf (373.82 KB)

Huang, B., London, B., Taskar, B. & Getoor, L. Empirical Analysis of Collective Stability. ICML Workshop on Structured Learning (SLG) (2013).

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huang-slg13.pdf (237.81 KB)

Huang, B., Kimmig, A., Getoor, L. & Golbeck, J. A Flexible Framework for Probabilistic Models of Social Trust. The 2013 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (SBP 2013) (2013).

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huang-sbp13.pdf (247.2 KB)

London, B., Huang, B. & Getoor, L. Graph-based Generalization Bounds for Learning Binary Relations. (2013).

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br_risk_bounds.pdf (304.54 KB)

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

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bach-uai13.pdf (379.45 KB)

Miao, H., Liu, X., Huang, B. & Getoor, L. A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization. 2013 IEEE International Conference on Big Data (2013).

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miao-bd13.pdf (307.51 KB)

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

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bach-fna13.pdf (210.09 KB)

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

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bach-inferning13.pdf (348.79 KB)

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

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ramesh-nipsws13.pdf (153.92 KB)

London, B., Rekatsinas, T., Huang, B. & Getoor, L. Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss. (2013).

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mrwtd.pdf (460.45 KB)

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

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london-nips13ws.pdf (205.57 KB)

2014

Ramakrishnan, N. et al. ‘Beating the news’ with EMBERS: Forecasting Civil Unrest using Open Source Indicators. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (2014).

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ramakrishnan-kdd14.pdf (1.15 MB)

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

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

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ramesh-aaai14.pdf (505.47 KB)

Fakhraei, S., Huang, B., Raschid, L. & 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)

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

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london-aistats14.pdf (490.14 KB)

Bach, S. H., Huang, B. & Getoor, L. Probabilistic Soft Logic for Social Good. KDD Workshop on Data Science for Social Good (2014).

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bach-dssg14.pdf (124.88 KB)

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

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bach-discml14.pdf (254.9 KB)

London, B., Huang, B. & Getoor, L. On the Strong Convexity of Variational Inference. NIPS Workshop on Advances in Variational Inference (2014).

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london-nips14ws.pdf (253.72 KB)

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

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Ramesh, A., Goldwasser, D., Huang, B., III, H. Daume & Getoor, L. Understanding MOOC Discussion Forums using Seeded LDA. 9th ACL Workshop on Innovative Use of NLP for Building Educational Applications (ACL, 2014).

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ramesh-aclws14.pdf (137.57 KB)

2015

London, B., Huang, B. & Getoor, L. The Benefits of Learning with Strongly Convex Approximate Inference. International Conference on Machine Learning (ICML) (2015).

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london-icml15.pdf (788.06 KB)

Bach, S. H., Broecheler, M., Huang, B. & 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)

Sridhar, D., Foulds, J., Walker, M., Huang, B. & Getoor, L. Joint Models of Disagreement and Stance in Online Debate. Annual Meeting of the Association for Computational Linguistics (ACL) (2015).

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sridhar-acl15.pdf (227.14 KB)

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

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bach-icml15.pdf (356.46 KB)

London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. – (2015).

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london-stability15.pdf (532.16 KB)

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

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bach-aistats15.pdf (345.2 KB)

2016

Muthiah, S. et al. Capturing Planned Protests from Open Source Indicators. AI Magazine 37, 63–75 (2016).

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muthiah-aimag16.pdf (1.23 MB)

London, B., Huang, B. & Getoor, L. Stability and Generalization in Structured Prediction. Journal of Machine Learning Research 17, (2016).

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london-jlmr17.pdf (532.8 KB)

2017

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

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bach-jmlr17.pdf (731.56 KB)

2019

Ramesh, A., Goldwasser, D., Huang, B., Daume-III, H. & Getoor, L. Interpretable Engagement Models for MOOCs using Hinge-loss Markov Random Fields. Transactions on Learning Technologies (2019).

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ramesh-tlt19.pdf (4.3 MB)

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