Ben London

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Lise GetoorProfessor of Computer Science, University of California, Santa CruzVerified email at ucsc.edu
Bert HuangAssistant Professor, Tufts University Department of Computer ScienceVerified email at vt.edu
Ben TaskarUniversity of WashingtonVerified email at cs.washington.edu
Stephen H. BachAssistant Professor of Computer Science, Brown UniversityVerified email at cs.brown.edu
Jay PujaraResearch Assistant Professor, University of Southern CaliforniaVerified email at cs.umd.edu
Sameh KhamisPrincipal Research Scientist, NvidiaVerified email at nvidia.com
Larry DavisProfessor of Computer Science, University of MarylandVerified email at cs.umd.edu
Theodoros RekatsinasApple, ETH ZurichVerified email at inf.ethz.ch
Sabina TomkinsAssistant Professor of Information, University of MichiganVerified email at umich.edu
Adrian WellerPrincipal Research Fellow, Machine Learning, University of CambridgeVerified email at eng.cam.ac.uk
Ofer MeshiResearch Scientist at GoogleVerified email at google.com
Ted SandlerGroundlight.aiVerified email at groundlight.ai
Thorsten JoachimsProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
William W. CohenGoogle AIVerified email at google.com
Alexander SchwingUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
David SontagProfessor, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Yi SuUniversity of California, BerkeleyVerified email at berkeley.edu
Luke Lequn WangCornell UniversityVerified email at cornell.edu
Adith SwaminathanMicrosoft ResearchVerified email at microsoft.com

Ben London

Sr. ML Scientist at Amazon

Verified email at amazon.com - Homepage

machine learning statistical learning theory structured prediction offline policy evaluation/learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Query-driven active surveying for collective classification G Namata, B London, L Getoor, B Huang, U Edu 10th International Workshop on Mining and Learning with Graphs 8, 1, 2012	228	2012
Hinge-loss Markov random fields: Convex inference for structured prediction S Bach, B Huang, B London, L Getoor arXiv preprint arXiv:1309.6813, 2013	138	2013
A PAC-Bayesian analysis of randomized learning with application to stochastic gradient descent B London Advances in Neural Information Processing Systems 30, 2017	52	2017
Collective stability in structured prediction: Generalization from one example B London, B Huang, B Taskar, L Getoor International Conference on Machine Learning, 828-836, 2013	50	2013
Stability and generalization in structured prediction B London, B Huang, L Getoor The Journal of Machine Learning Research 17 (1), 7808-7859, 2016	43	2016
Collective Classification of Network Data. B London, L Getoor Data Classification: Algorithms and Applications 399, 2014	42	2014
PAC-Bayesian collective stability B London, B Huang, B Taskar, L Getoor Artificial Intelligence and Statistics, 585-594, 2014	28	2014
Collective activity detection using hinge-loss Markov random fields B London, S Khamis, S Bach, B Huang, L Getoor, L Davis Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013	28	2013
Sustainability at scale: towards bridging the intention-behavior gap with sustainable recommendations S Tomkins, S Isley, B London, L Getoor Proceedings of the 12th ACM conference on recommender systems, 214-218, 2018	24	2018
Multi-relational learning using weighted tensor decomposition with modular loss B London, T Rekatsinas, B Huang, L Getoor arXiv preprint arXiv:1303.1733, 2013	24	2013
Collective graph identification GM Namata, B London, L Getoor ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (3), 1-36, 2016	20	2016
Reducing label cost by combining feature labels and crowdsourcing J Pujara, B London, L Getoor ICML workshop on Combining learning strategies to reduce label cost, 2011	15	2011
Budgeted online collective inference J Pujara, B London, L Getoor UAI, 2015	12	2015
Bayesian counterfactual risk minimization B London, T Sandler International Conference on Machine Learning, 4125-4133, 2019	11	2019
Improved generalization bounds for large-scale structured prediction B London, B Huang, L Getoor NIPS workshop on algorithmic and statistical approaches for large social …, 2012	11	2012
Generalization bounds for randomized learning with application to stochastic gradient descent B London NIPS Workshop on Optimizing the Optimizers, 2016	10	2016
The benefits of learning with strongly convex approximate inference B London, B Huang, L Getoor International Conference on Machine Learning, 410-418, 2015	9	2015
Online inference for knowledge graph construction J Pujara, B London, L Getoor, WW Cohen Fifth International Workshop on Statistical Relational AI, www …, 2015	9	2015
Pac-bayes generalization bounds for randomized structured prediction B London, B Huang, B Taskar, L Getoor NIPS Workshop on Perturbation, Optimization and Statistics, 2013	8	2013
PAC identifiability in federated personalization B London NeurIPS 2020 Workshop on Scalability, Privacy and Security in Federated …, 2020	4	2020

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