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

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Filters: Author is London, Ben  [Clear All Filters]
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B. London, Huang, B., and Getoor, L., “Graph-based Generalization Bounds for Learning Binary Relations”. University of Maryland College Park, 2013.PDF icon br_risk_bounds.pdf (304.54 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)
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B. London, Huang, B., and Getoor, L., “Improved Generalization Bounds for Large-scale Structured Prediction”, in NIPS Workshop on Algorithmic and Statistical Approaches for Large Social Networks, 2012.PDF icon london-nips12ws.pdf (213.95 KB)
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B. London, Rekatsinas, T., Huang, B., and Getoor, L., “Multi-relational Learning Using Weighted Tensor Decomposition with Modular Loss”. University of Maryland College Park, 2013.PDF icon mrwtd.pdf (460.45 KB)
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J. Pujara, London, B., Getoor, L., and Cohen, W., “Online Inference for Knowledge Graph Construction.”, in Workshop on Statistical Relational AI, 2015.PDF icon pujara-starai15.pdf (340.95 KB)
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B. London, Huang, B., Taskar, B., and Getoor, L., “PAC-Bayes Generalization Bounds for Randomized Structured Prediction”, in NIP Workshop on Perturbation, Optimization and Statistics, 2013.PDF icon london-nips13ws.pdf (205.57 KB)
B. London, Huang, B., Taskar, B., and Getoor, L., “PAC-Bayesian Collective Stability”, in Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 2014.PDF icon london-aistats14.pdf (490.14 KB)
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J. Pujara, London, B., and Getoor, L., “Reducing Label Cost by Combining Feature Labels and Crowdsourcing”, in ICML Workshop on Combining Learning Strategies to Reduce Label Cost, 2011.PDF icon clsicml_pujara_london.pdf (253.29 KB)
S
B. London, Huang, B., and Getoor, L., “Stability and Generalization in Structured Prediction”, –, 2015.PDF icon london-stability15.pdf (532.16 KB)
B. London, “On the Stability of Structured Prediction”, University of Maryland, 2015.PDF icon blondon-thesis.pdf (1.16 MB)
B. London, Huang, B., and Getoor, L., “On the Strong Convexity of Variational Inference”, in NIPS Workshop on Advances in Variational Inference, 2014.PDF icon london-nips14ws.pdf (253.72 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.PDF icon tomkins-recsys18.pdf (655.92 KB)