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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

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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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2020

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)

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)

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)

V. Embar, Srinivasan, S., and Getoor, L., “Estimating Aggregate Properties In Relational Networks With Unobserved Data”, in AAAI Workshop on Statistical Relational Artificial Intelligence (StarAI), 2020.

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embar-starai20.pdf (257.9 KB)

S. Srinivasan, Augustine, E., and Getoor, L., “Tandem Inference: An Out-of-Core Streaming Algorithm For Very Large-Scale Relational Inference”, in AAAI Conference on Artificial Intelligence (AAAI), 2020.

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srinivasan-aaai20b.pdf (506.62 KB)

2019

A. Kimmig, Memory, A., Miller, R. J., and Getoor, L., “A Collective, Probabilistic Approach to Schema Mapping Using Diverse Noisy Evidence”, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 31, no. 8, p. 1426--1439, 2019.

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kimming-tkde19.pdf (713.64 KB)

G. Farnadi, Babaki, B., and Getoor, L., “A Declarative Approach to Fairness in Relational Domains”, IEEE Data Engineering Bulletin, vol. 42, no. 3, p. 36--48, 2019.

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farnadi-de19.pdf (365.14 KB)

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)

D. Sridhar and Getoor, L., “Estimating Causal Effects of Tone in Online Debates”, in International Joint Conference on Artificial Intelligence (IJCAI), 2019.

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sridhar-ijcai19.pdf (220.49 KB)

P. Kouki, Schaffer, J., Pujara, J., O'Donovan, J., and Getoor, L., “Generating and Understanding Personalized Explanations in Hybrid Recommender Systems”, ACM Transactions on Interactive Intelligent Systems, 2019.

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kouki-tiis19.pdf (2.01 MB)

S. Srinivasan, Rao, N. S., Subbaian, K., and Getoor, L., “Identifying Facet Mismatches In Search Via Micrographs”, in International Conference on Information and Knowledge Management (CIKM), 2019.

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srinivasan-cikm19.pdf (887.06 KB)

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)

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)

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)

V. Embar, Srinivasan, S., and Getoor, L., “Tractable Marginal Inference for Hinge-Loss Markov Random Fields”, in ICML Workshop on Tractable Probabilistic Modeling (TPM), 2019.

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embar-tpm19.pdf (410.24 KB)

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)

S. Tomkins and Getoor, L., “Understanding Hybrid-MOOC Effectiveness with a Collective Socio-Behavioral Model”, Journal of Educational Data Mining (JEDM), vol. 11, p. 42--77, 2019.

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tomkins-jedm19.pdf (679.09 KB)

2018

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)

G. Farnadi, Kouki, P., Thompson, S. K., Srinivasan, S., and Getoor, L., “A Fairness-aware Hybrid Recommender System”, in RecSys Workshop on Responsible Recommendation (FATREC), 2018.

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farnadi-fatrec18.pdf (474.04 KB)

S. Tomkins, Getoor, L., Chen, Y., and Zhang, Y., “A Socio-linguistic Model for Cyberbullying Detection”, in International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018.

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tomkins-asonam18.pdf (299.34 KB)

Y. Zhang, Ramesh, A., Golbeck, J., Sridhar, D., and Getoor, L., “A Structured Approach to Understanding Recovery and Relapse in AA”, in The Web Conference (WWW), 2018.

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zhang-www18.pdf (800.66 KB)

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)

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)

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)

D. Sridhar, Springer, A., Hollis, V., Whittaker, S., and Getoor, L., “Estimating Causal Effects of Exercise from Mood Logging Data”, in ICML Workshop on Causal Machine Learning (CausalML), 2018.

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sridhar-causalml18.pdf (333.69 KB)

G. Farnadi, Babaki, B., and Getoor, L., “Fairness in Relational Domains”, in Artificial Intelligence, Ethics, and Society (AIES), 2018.

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farnadi_aies2018.pdf (418.24 KB)

G. Farnadi, Babaki, B., and Getoor, L., “Fairness-aware Relational Learning and Inference”, in AAAI Workshop on Declarative Learning Based Programming (DeLBP), 2018.

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farnadi-delbp2018.pdf (169.37 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)

P. Kouki, “Resolution, Recommendation, and Explanation in Richly Structured Social Networks”, 2018.

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kouki-dissertation.pdf (6.94 MB)

D. Sridhar, Pujara, J., and Getoor, L., “Scalable Probabilistic Causal Structure Discovery”, in International Joint Conference on Artificial Intelligence (IJCAI), 2018.

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sridhar-ijcai18.pdf (281.32 KB)

V. Embar, Sridhar, D., Farnadi, G., and Getoor, L., “Scalable Structure Learning for Probabilistic Soft Logic”, in IJCAI Workshop on Statistical Relational AI (StarAI), 2018.

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embar-starai18.pdf (400.23 KB)

S. Tomkins, Isley, S., London, B., and Getoor, L., “Sustainability at Scale: Bridging the Intention-Behavior Gap with Sustainable Recommendations”, in Recommender Systems (RecSys), 2018.

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tomkins-recsys18.pdf (655.92 KB)

S. Tomkins, Farnadi, G., Amantullah, B., Getoor, L., and Minton, S., “The Impact of Environmental Stressors on Human Trafficking”, in ICWSM Workshop on Beyond Online Data (BOD), 2018.

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tomkins-bod18.pdf (473.58 KB)

S. Tomkins, Farnadi, G., Amantullah, B., Getoor, L., and Minton, S., “The Impact of Environmental Stressors on Human Trafficking”, in International Conference on Data Mining (ICDM), 2018.

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tomkins-icdm18.pdf (473.58 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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2017

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)

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. Tomkins, Getoor, L., Chen, Y., and Zhang, Y., “Detecting Cyber-bullying from Sparse Data and Inconsistent Labels”, in Learning with Limited Labeled Data (LLD) NIPS Workshop, 2017.

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tomkins-NIPSLLD17.pdf (286.95 KB)

S. Tomkins, Pujara, J., and Getoor, L., “Disambiguating Energy Disaggregation: A Collective Probabilistic Approach”, in International Joint Conference on Artificial Intelligence, 2017.

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tomkins-ijcai17.pdf (373.28 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)

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)

S. Kim, Kini, N., Pujara, J., Koh, E., and Getoor, L., “Probabilistic Visitor Stitching on Cross-Device Web Logs”, in International Conference on World Wide Web (WWW), 2017, pp. 1581–1589.

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p1581-kimwww17.pdf (1.23 MB)

G. Farnadi, Bach, S. H., Moens, M. - F., Getoor, L., and De Cock, M., “Soft quantification in statistical relational learning”, Machine Learning Journal, 2017.

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farnadi-mlj17.pdf (1.24 MB)

J. Pujara, Augustine, E., and Getoor, L., “Sparsity and Noise: Where Knowledge Graph Embeddings Fall Short”, in Conference on Empirical Methods in Natural Language Processing (EMNLP), 2017.

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pujara-emnlp17.pdf (677.74 KB)

P. Kouki, Schaffer, J., Pujara, J., ODonovan, J., and Getoor, L., “User Preferences for Hybrid Explanations”, in 11th ACM Conference on Recommender Systems (RecSys), 2017.

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kouki-recsys17.pdf (2.64 MB)

D. Sridhar, Pujara, J., and Getoor, L., “Using Noisy Extractions to Discover Causal Knowledge”, in NIPS Workshop on Automated Knowledge Base Construction, 2017.

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sridhar-akbc17.pdf (203.34 KB)

2016

D. Sridhar, Fakhraei, S., and Getoor, L., “A Probabilistic Approach for Collective Similarity-based Drug-Drug Interaction Prediction”, Bioinformatics, vol. 32, 2016.

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sridhar-bioinformatics16.pdf (1.94 MB)

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)

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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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)

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