Ben London

Citirano

	Sve	Od 2017.
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Lise GetoorProfessor of Computer Science, University of California, Santa CruzPotvrđena adresa e-pošte na ucsc.edu
Bert HuangAssistant Professor, Tufts University Department of Computer SciencePotvrđena adresa e-pošte na vt.edu
Ben TaskarUniversity of WashingtonPotvrđena adresa e-pošte na cs.washington.edu
Stephen H. BachAssistant Professor of Computer Science, Brown UniversityPotvrđena adresa e-pošte na cs.brown.edu
Jay PujaraResearch Assistant Professor, University of Southern CaliforniaPotvrđena adresa e-pošte na cs.umd.edu
Sameh KhamisPrincipal Research Scientist, NvidiaPotvrđena adresa e-pošte na nvidia.com
Larry DavisProfessor of Computer Science, University of MarylandPotvrđena adresa e-pošte na cs.umd.edu
Theodoros RekatsinasApple, ETH ZurichPotvrđena adresa e-pošte na inf.ethz.ch
Ted SandlerGroundlight.aiPotvrđena adresa e-pošte na groundlight.ai
Sabina TomkinsAssistant Professor of Information, University of MichiganPotvrđena adresa e-pošte na umich.edu
Adrian WellerPrincipal Research Fellow, Machine Learning, University of CambridgePotvrđena adresa e-pošte na eng.cam.ac.uk
Ofer MeshiResearch Scientist at GooglePotvrđena adresa e-pošte na google.com
Thorsten JoachimsProfessor of Computer Science, Cornell UniversityPotvrđena adresa e-pošte na cs.cornell.edu
William W. CohenGoogle AIPotvrđena adresa e-pošte na google.com
Alexander SchwingUniversity of Illinois at Urbana-ChampaignPotvrđena adresa e-pošte na illinois.edu
David SontagProfessor, Massachusetts Institute of TechnologyPotvrđena adresa e-pošte na csail.mit.edu
Yi SuGooglePotvrđena adresa e-pošte na google.com
Luke Lequn WangCornell UniversityPotvrđena adresa e-pošte na cornell.edu
Adith SwaminathanMicrosoft ResearchPotvrđena adresa e-pošte na microsoft.com

Prati

Ben London

Sr. ML Scientist at Amazon

Potvrđena adresa e-pošte na amazon.com - Početna stranica

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


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
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	239	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
Collective Classification of Network Data. B London, L Getoor Data Classification: Algorithms and Applications 399, 2014	45	2014
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
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	26	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
Bayesian counterfactual risk minimization B London, T Sandler International Conference on Machine Learning, 4125-4133, 2019	12	2019
Budgeted online collective inference J Pujara, B London, L Getoor UAI, 2015	12	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	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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