Archived Publications (Latest: https://linqs.github.io/linqs-website/publications/)

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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)
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G. Farnadi, Bach, S. H., Blondeel, M., Moens, M. - F., Getoor, L., and De Cock, M., “Statistical Relational Learning with Soft Quantifiers”, in International Conference on Inductive Logic Programming (ILP), 2015.PDF icon farnadi-ilp15.pdf (578.43 KB)
G. Farnadi, Bach, S. H., Moens, M. - F., Getoor, L., and De Cock, M., “Soft quantification in statistical relational learning”, Machine Learning Journal, 2017.PDF icon farnadi-mlj17.pdf (1.24 MB)
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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)
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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., 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)
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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. 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)
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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, “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, 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)
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A. Memory, Kimmig, A., Bach, S. H., Raschid, L., and Getoor, L., “Graph Summarization in Annotated Data Using Probabilistic Soft Logic”, in Proceedings of the International Workshop on Uncertainty Reasoning for the Semantic Web (URSW), 2012.PDF icon mrc_iswc12_ws.pdf (411.71 KB)
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G. Farnadi, Bach, S. H., Moens, M. - F., Getoor, L., and De Cock, M., “Extending PSL with Fuzzy Quantifiers”, in International Workshop on Statistical Relational Artificial Intelligence (StaRAI), 2014.PDF icon farnadi-starai14.pdf (196.15 KB)
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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)