Ben London

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Lise GetoorDistinguished Professor of Computer Science & Engineering, 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
Thorsten JoachimsProfessor of Computer Science, Cornell UniversityVerified email at cs.cornell.edu
Stephen H. BachAssistant Professor of Computer Science, Brown UniversityVerified email at cs.brown.edu
Jay PujaraResearch Associate Professor, University of Southern CaliforniaVerified email at cs.umd.edu
Ted SandlerAmazon.comVerified email at amazon.com
Larry DavisProfessor of Computer Science, University of MarylandVerified email at cs.umd.edu
Theodoros RekatsinasAppleVerified email at inf.ethz.ch
Sabina TomkinsAssistant Professor of Information, University of MichiganVerified email at umich.edu
Sameh KhamisCo-Founder and Director of R&D, RembrandVerified email at rembrand.com
Adrian WellerDirector of Research, Machine Learning, University of CambridgeVerified email at eng.cam.ac.uk
Ofer MeshiResearch Scientist at GoogleVerified email at google.com
Yi SuGoogle DeepmindVerified email at google.com
Adith SwaminathanNetflixVerified email at netflix.com
William W. CohenCMU and Google DeepMindVerified email at google.com
David SontagProfessor, Massachusetts Institute of TechnologyVerified email at csail.mit.edu
Alexander SchwingUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu

Ben London

Principal Scientist at Amazon

Verified email at amazon.com - Homepage

machine learning statistical learning theory structured prediction offline policy evaluation


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	636	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	147	2013
A PAC-Bayesian analysis of randomized learning with application to stochastic gradient descent B London Advances in Neural Information Processing Systems 30, 2017	83	2017
Collective graph identification GM Namata, B London, L Getoor ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (3), 1-36, 2016	66	2016
Stability and generalization in structured prediction B London, B Huang, L Getoor Journal of Machine Learning Research 17 (221), 1-52, 2016	61	2016
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	59	2018
Collective Classification of Network Data. B London, L Getoor Data Classification: Algorithms and Applications 399, 2014	58	2014
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	56	2013
Bayesian counterfactual risk minimization B London, T Sandler International Conference on Machine Learning, 4125-4133, 2019	40	2019
Collective activity detection using hinge-loss Markov random fields B London, S Khamis, SH Bach, B Huang, L Getoor, L Davis 2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops …, 2013	33	2013
PAC-Bayesian collective stability B London, B Huang, B Taskar, L Getoor Artificial Intelligence and Statistics, 585-594, 2014	32	2014
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
Recommendations as treatments T Joachims, B London, Y Su, A Swaminathan, L Wang AI Magazine 42 (3), 19-30, 2021	21	2021
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, 712-721, 2015	14	2015
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	12	2012
Generalization bounds for randomized learning with application to stochastic gradient descent B London	11	2017
The benefits of learning with strongly convex approximate inference B London, B Huang, L Getoor International Conference on Machine Learning, 410-418, 2015	10	2015
Online inference for knowledge graph construction J Pujara, B London, L Getoor, WW Cohen Workshop on statistical relational AI, 2015	9	2015
Tutorials at the web conference 2023 V Fionda, O Hartig, R Abdolazimi, S Amer-Yahia, H Chen, X Chen, P Cui, ... Companion Proceedings of the ACM Web Conference 2023, 648-658, 2023	7	2023

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