Tengyu MA

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Sanjeev AroraProfessor of Computer Science, Princeton UniversityVerified email at cs.princeton.edu
Rong GeDuke UniversityVerified email at cs.duke.edu
Yingyu LiangUniversity of Wisconsin-MadisonVerified email at cs.wisc.edu
Colin WeiStanford UniversityVerified email at stanford.edu
Yuanzhi LiAssistant Professor at CMUVerified email at andrew.cmu.edu
Jason D. LeeAssistant Professor of Electrical Engineering, Princeton UniversityVerified email at princeton.edu
Andrej RisteskiCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Elad HazanProfessor at Princeton University and Director Google AI PrincetonVerified email at cs.princeton.edu
Aditya BhaskaraUniversity of UtahVerified email at cs.utah.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Adrien GaidonHead of Machine Learning Research, Toyota Research Institute (TRI)Verified email at tri.global
Brian BullinsResearch Assistant Professor, TTI ChicagoVerified email at ttic.edu
Moritz HardtUniversity of California, BerkeleyVerified email at berkeley.edu
Yuping LuoComputer Science Department, Princeton UniversityVerified email at cs.princeton.edu
Yining ChenStanford UniversityVerified email at stanford.edu
Yann N. DauphinGoogle AIVerified email at dauphin.io
Kaidi CaoStanford UniversityVerified email at cs.stanford.edu
Nikos ArechigaToyota Research InstituteVerified email at tri.global
Stefano ErmonStanford UniversityVerified email at cs.stanford.edu
Garrett ThomasStanford UniversityVerified email at stanford.edu

Tengyu MA

Stanford University

Verified email at stanford.edu - Homepage

Machine Learning Deep Learning Theory Machine Learning Theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A simple but tough-to-beat baseline for sentence embeddings S Arora, Y Liang, T Ma ICLR 2017, 2016	988	2016
Matrix Completion has No Spurious Local Minimum R Ge, JD Lee, T Ma NIPS 2016 (best student paper). arXiv preprint arXiv:1605.07272, 2016	539	2016
Generalization and Equilibrium in Generative Adversarial Nets (GANs) S Arora, R Ge, Y Liang, T Ma, Y Zhang ICML 2017;arXiv preprint arXiv:1703.00573, 2017, 2017	513	2017
Provable bounds for learning some deep representations S Arora, A Bhaskara, R Ge, T Ma International conference on machine learning, 584-592, 2014	372	2014
A latent variable model approach to pmi-based word embeddings S Arora, Y Li, Y Liang, T Ma, A Risteski Transactions of the Association for Computational Linguistics 4, 385-399, 2016	342*	2016
Identity Matters in Deep Learning M Hardt, T Ma ICLR 2017, 2016	282	2016
Learning imbalanced datasets with label-distribution-aware margin loss K Cao, C Wei, A Gaidon, N Arechiga, T Ma arXiv preprint arXiv:1906.07413, 2019	280	2019
Finding Approximate Local Minima for Nonconvex Optimization in Linear Time N Agarwal, Z Allen-Zhu, B Bullins, E Hazan, T Ma STOC 2017, 2016	267*	2016
Learning one-hidden-layer neural networks with landscape design R Ge, JD Lee, T Ma ICLR 2017; arXiv preprint arXiv:1711.00501, 2017	207	2017
Gradient descent learns linear dynamical systems M Hardt, T Ma, B Recht arXiv preprint arXiv:1609.05191, 2016	205	2016
Simple, efficient, and neural algorithms for sparse coding S Arora, R Ge, T Ma, A Moitra Conference on Learning Theory (COLT) 2015. arXiv preprint arXiv:1503.00778, 2015	189	2015
Algorithmic Regularization in Over-parameterized Matrix Recovery and Neural Networks with Quadratic Activations Y Li, T Ma, H Zhang COLT 2018 (best paper); arXiv preprint arXiv:1712.09203, 2017	178*	2017
Linear algebraic structure of word senses, with applications to polysemy S Arora, Y Li, Y Liang, T Ma, A Risteski arXiv preprint arXiv:1601.03764, 2016	164	2016
Fixup initialization: Residual learning without normalization H Zhang, YN Dauphin, T Ma arXiv preprint arXiv:1901.09321, 2019	159	2019
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel TM Colin Wei, Jason D. Lee, Qiang Liu arXiv preprint arXiv:1810.05369, 2019	151*	2019
Communication lower bounds for statistical estimation problems via a distributed data processing inequality M Braverman, A Garg, T Ma, HL Nguyen, DP Woodruff 48th Annual Symposium on the Theory of Computing (STOC), 2016. arXiv …, 2015	121	2015
Mopo: Model-based offline policy optimization T Yu, G Thomas, L Yu, S Ermon, J Zou, S Levine, C Finn, T Ma arXiv preprint arXiv:2005.13239, 2020	119	2020
Algorithmic framework for model-based deep reinforcement learning with theoretical guarantees Y Luo, H Xu, Y Li, Y Tian, T Darrell, T Ma arXiv preprint arXiv:1807.03858, 2018	108	2018
Towards explaining the regularization effect of initial large learning rate in training neural networks Y Li, C Wei, T Ma arXiv preprint arXiv:1907.04595, 2019	107	2019
Distributed stochastic variance reduced gradient methods by sampling extra data with replacement JD Lee, Q Lin, T Ma, T Yang The Journal of Machine Learning Research 18 (1), 4404-4446, 2017	105*	2017

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