Zeyuan Allen-Zhu （朱澤園）

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Yuanzhi LiAssistant Professor at CMUVerified email at andrew.cmu.edu
Lorenzo OrecchiaUniversity of Chicago, Computer ScienceVerified email at bu.edu
Elad HazanProfessor at Princeton University and Director Google AI PrincetonVerified email at cs.princeton.edu
Yang YuanMassachusetts Institute of TechnologyVerified email at cs.cornell.edu
Weizhu ChenMicrosoftVerified email at microsoft.com
Alessandro ChiesaUC BerkeleyVerified email at berkeley.edu
Zhao SongAdobe ResearchVerified email at ias.edu
zheng chenPrinciple Researcher of Microsoft Research AsiaVerified email at microsoft.com
Chenguang ZhuPrincipal Research Manager at Microsoft ResearchVerified email at microsoft.com
Sebastien BubeckSr Principal Research Manager, ML Foundations group, Microsoft ResearchVerified email at microsoft.com
Naman AgarwalSenior Research Scientist, Google AI PrincetonVerified email at google.com
Tengyu MAStanford UniversityVerified email at stanford.edu
Brian BullinsResearch Assistant Professor, TTI-ChicagoVerified email at ttic.edu
Silvio LattanziResearch Scientist at GoogleVerified email at google.com
Vahab MirrokniDistinguished Scientist, Google Research, New YorkVerified email at google.com
Zhenyu LiaoApplied Scientist in Amazon Inc.Verified email at amazon.com
Pinyan LuITCS, Shanghai University of Finance and EconomicsVerified email at mail.shufe.edu.cn
Xiaorui SunUniversity of Illinois at ChicagoVerified email at uic.edu
Aarti SinghAssociate Professor of Machine Learning Department, Carnegie Mellon UniversityVerified email at cmu.edu
Yingyu LiangUniversity of Wisconsin-MadisonVerified email at cs.wisc.edu

Zeyuan Allen-Zhu （朱澤園）

Microsoft Research Redmond

Verified email at csail.mit.edu - Homepage

Machine Learning Optimization Algorithms Theory


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A convergence theory for deep learning via over-parameterization Z Allen-Zhu, Y Li, Z Song ICML 2019: International Conference on Machine Learning, 2019	892	2019
Katyusha: the first direct acceleration of stochastic gradient methods Z Allen-Zhu STOC 2017: Symposium on Theory of Computing, 19-23, 2017	524	2017
Learning and generalization in overparameterized neural networks, going beyond two layers Z Allen-Zhu, Y Li, Y Liang NeurIPS 2019: Neural Information Processing Systems, 2019	523	2019
Is Q-learning Provably Efficient? C Jin, Z Allen-Zhu, S Bubeck, MI Jordan NIPS 2018: Neural Information Processing Systems, 2018	516	2018
Variance reduction for faster non-convex optimization Z Allen-Zhu, E Hazan ICML 2016: International Conference on Machine Learning, 699-707, 2016	355	2016
Linear coupling: An ultimate unification of gradient and mirror descent Z Allen-Zhu, L Orecchia ITCS 2017: Innovations in Theoretical Computer Science, 2017	320*	2017
Finding approximate local minima faster than gradient descent N Agarwal, Z Allen-Zhu, B Bullins, E Hazan, T Ma STOC 2017: Symposium on Theory of Computing, 1195-1199, 2017	285*	2017
A simple, combinatorial algorithm for solving SDD systems in nearly-linear time JA Kelner, L Orecchia, A Sidford, ZA Zhu STOC 2013: Symposium on Theory of Computing, 911-920, 2013	255	2013
Natasha 2: Faster Non-Convex Optimization Than SGD Z Allen-Zhu NIPS 2018: Neural Information Processing Systems, 2018	208	2018
Byzantine Stochastic Gradient Descent D Alistarh, Z Allen-Zhu, J Li NIPS 2018: Neural Information Processing Systems, 2018	197	2018
Improved SVRG for non-strongly-convex or sum-of-non-convex objectives Z Allen-Zhu, Y Yuan ICML 2016: International Conference on Machine Learning, 1080-1089, 2016	184	2016
Even faster accelerated coordinate descent using non-uniform sampling Z Allen-Zhu, Z Qu, P Richtárik, Y Yuan ICML 2016: International Conference on Machine Learning, 1110-1119, 2016	166	2016
Asymptotically optimal strategy-proof mechanisms for two-facility games P Lu, X Sun, Y Wang, ZA Zhu ACM-EC 2010: Conference on Economics and Computation, 315-324, 2010	156	2010
On the convergence rate of training recurrent neural networks Z Allen-Zhu, Y Li, Z Song NeurIPS 2019: Neural Information Processing Systems, 2019	127	2019
A novel click model and its applications to online advertising ZA Zhu, W Chen, T Minka, C Zhu, Z Chen WSDM 2010: International Conference on Web Search and Data Mining, 321-330, 2010	119	2010
Randomized accuracy-aware program transformations for efficient approximate computations ZA Zhu, S Misailovic, JA Kelner, M Rinard POPL 2012: Symposium on Principles of Programming Languages, 441-454, 2012	115	2012
What Can ResNet Learn Efficiently, Going Beyond Kernels? Z Allen-Zhu, Y Li NeurIPS 2019: Neural Information Processing Systems, 2019	111	2019
Neon2: Finding Local Minima via First-Order Oracles Z Allen-Zhu, Y Li NIPS 2018: Neural Information Processing Systems, 2018	110	2018
LazySVD: Even faster SVD decomposition yet without agonizing pain Z Allen-Zhu, Y Li NIPS 2016: Neural Information Processing Systems, 974-982, 2016	108	2016
Much faster algorithms for matrix scaling Z Allen-Zhu, Y Li, R Oliveira, A Wigderson FOCS 2017: Symposium on Foundations of Computer Science, 2017	94	2017

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