John Duchi

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Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyDirección de correo verificada de cs.berkeley.edu
Hongseok NamkoongColumbia UniversityDirección de correo verificada de columbia.edu
Yair CarmonTel Aviv UniversityDirección de correo verificada de tauex.tau.ac.il
Alekh AgarwalGoogleDirección de correo verificada de google.com
Feng RuanDepartment of EECS, University of California, BerkeleyDirección de correo verificada de berkeley.edu
Aman SinhaStanford UniversityDirección de correo verificada de stanford.edu
Aaron SidfordStanford UniversityDirección de correo verificada de stanford.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityDirección de correo verificada de cs.stanford.edu
Hilal AsiApple ML ResearchDirección de correo verificada de apple.com
Yuchen ZhangResearch Scientist at ByteDanceDirección de correo verificada de microsoft.com
Oliver HinderAssistant Professor, Industrial Engineering Department, University of PittsburghDirección de correo verificada de pitt.edu
Elad HazanProfessor at Princeton University and Director Google AI PrincetonDirección de correo verificada de princeton.edu
Aditi RaghunathanAssistant professor, Carnegie Mellon UniversityDirección de correo verificada de cmu.edu
Shai Shalev-ShwartzThe Hebrew UniversityDirección de correo verificada de cs.huji.ac.il
Riccardo VolpiArsenale BioYardsDirección de correo verificada de arsenale.bio
Maxime CauchoisPhD Student, Stanford UniversityDirección de correo verificada de stanford.edu
Tushar ChandraGoogleDirección de correo verificada de google.com
Ryan RogersLinkedInDirección de correo verificada de linkedin.com
Sang Michael XiePhD Candidate, Stanford UniversityDirección de correo verificada de cs.stanford.edu
Peter BartlettProfessor, EECS and Statistics, UC BerkeleyDirección de correo verificada de cs.berkeley.edu

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John Duchi

Associate Professor of Statistics and Electrical Engineering, Stanford University

Dirección de correo verificada de stanford.edu - Página principal

Machine learning statistics optimization artificial intelligence


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Adaptive subgradient methods for online learning and stochastic optimization. J Duchi, E Hazan, Y Singer Journal of machine learning research 12 (7), 2011	14192	2011
Efficient projections onto the l₁-ball for learning in high dimensions J Duchi, S Shalev-Shwartz, Y Singer, T Chandra Proceedings of the 25th international conference on Machine learning, 272-279, 2008	1722	2008
Dual averaging for distributed optimization: Convergence analysis and network scaling JC Duchi, A Agarwal, MJ Wainwright IEEE Transactions on Automatic control 57 (3), 592-606, 2011	1407	2011
Local privacy and statistical minimax rates JC Duchi, MI Jordan, MJ Wainwright 2013 IEEE 54th annual symposium on foundations of computer science, 429-438, 2013	1367	2013
Certifying some distributional robustness with principled adversarial training A Sinha, H Namkoong, R Volpi, J Duchi arXiv preprint arXiv:1710.10571, 2017	1151	2017
Generalizing to unseen domains via adversarial data augmentation R Volpi, H Namkoong, O Sener, JC Duchi, V Murino, S Savarese Advances in neural information processing systems 31, 2018	862	2018
Unlabeled data improves adversarial robustness Y Carmon, A Raghunathan, L Schmidt, JC Duchi, PS Liang Advances in neural information processing systems 32, 2019	788	2019
Efficient online and batch learning using forward backward splitting J Duchi, Y Singer The Journal of Machine Learning Research 10, 2899-2934, 2009	788	2009
Distributed delayed stochastic optimization A Agarwal, JC Duchi Advances in neural information processing systems 24, 2011	762	2011
Communication-efficient algorithms for statistical optimization Y Zhang, MJ Wainwright, JC Duchi Advances in neural information processing systems 25, 2012	646	2012
Optimal rates for zero-order convex optimization: The power of two function evaluations JC Duchi, MI Jordan, MJ Wainwright, A Wibisono IEEE Transactions on Information Theory 61 (5), 2788-2806, 2015	522	2015
MLbase: A Distributed Machine-learning System. T Kraska, A Talwalkar, JC Duchi, R Griffith, MJ Franklin, MI Jordan Cidr 1, 2-1, 2013	477	2013
Minimax optimal procedures for locally private estimation JC Duchi, MI Jordan, MJ Wainwright Journal of the American Statistical Association 113 (521), 182-201, 2018	462	2018
Protection against reconstruction and its applications in private federated learning A Bhowmick, J Duchi, J Freudiger, G Kapoor, R Rogers arXiv preprint arXiv:1812.00984, 2018	425	2018
Learning models with uniform performance via distributionally robust optimization JC Duchi, H Namkoong The Annals of Statistics 49 (3), 1378-1406, 2021	418	2021
Composite objective mirror descent. JC Duchi, S Shalev-Shwartz, Y Singer, A Tewari Colt 10, 14-26, 2010	415	2010
Divide and conquer kernel ridge regression: A distributed algorithm with minimax optimal rates Y Zhang, J Duchi, M Wainwright The Journal of Machine Learning Research 16 (1), 3299-3340, 2015	396	2015
Variance-based regularization with convex objectives J Duchi, H Namkoong Journal of Machine Learning Research 20 (68), 1-55, 2019	393	2019
Statistics of robust optimization: A generalized empirical likelihood approach JC Duchi, PW Glynn, H Namkoong Mathematics of Operations Research 46 (3), 946-969, 2021	379	2021
Stochastic gradient methods for distributionally robust optimization with f-divergences H Namkoong, JC Duchi Advances in neural information processing systems 29, 2016	356	2016

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