Publications

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S. H. Bach, Huang, B., and Getoor, L., Probabilistic Soft Logic for Social Good, in KDD Workshop on Data Science for Social Good, 2014.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon bhattacharyasdm06.pdf (209.24 KB)
I. Bhattacharya, Collective Entity Resolution In Relational Data, University of Maryland, College Park, 2006.PDF icon thesis.pdf (761.21 KB)
I. Bhattacharya and Getoor, L., Collective Entity Resolution in Relational Data, Data Engineering Bulletin, vol. 29, 2006.
I. Bhattacharya and Getoor, L., Entity Resolution in Social Networks, in International Sunbelt Social Network Conference (Sunbelt XXVI), 2006.
I. Bhattacharya and Getoor, L., Entity Resolutions in Graphs, 1st ed., vol. 1. Wiley, 2006, p. 311--344.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon bilgic-icml10.pdf (515.65 KB)
M. Bilgic, Information Acquisition in Structured Domains, University of Maryland - College Park, 2010.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.PDF icon 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.
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.PDF icon ddupe.pdf (224.93 KB)
S. Bradley and Getoor, L., Topic Modeling for Wikipedia Link Disambiguation, ACM Transactions on Information Systems, vol. 32, 2014.
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.PDF icon broecheler-nips10.pdf (382.51 KB)
M. Broecheler, Mihalkova, L., and Getoor, L., Probabilistic Similarity Logic, in Conference on Uncertainty in Artificial Intelligence, 2010.PDF icon broecheler-uai10.pdf (399.54 KB)
M. Broecheler and Getoor, L., Probabilistic Similarity Logic, in International Workshop on Statistical Relational Learning (SRL'09), 2009.PDF icon broecheler-srl09.pdf (176.13 KB)

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