Tengyu MA

Citirano

	Sve	Od 2019.
Citati	22261	20330
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i10-indeks	105	105

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Suautori

Colin WeiStanford UniversityPotvrđena adresa e-pošte na stanford.edu
Sanjeev AroraProfessor of Computer Science, Princeton UniversityPotvrđena adresa e-pošte na cs.princeton.edu
Rong GeDuke UniversityPotvrđena adresa e-pošte na cs.duke.edu
Percy LiangAssociate Professor of Computer Science, Stanford UniversityPotvrđena adresa e-pošte na cs.stanford.edu
Yuanzhi LiAssistant Professor at CMUPotvrđena adresa e-pošte na andrew.cmu.edu
Jason D. LeeAssociate Professor of Electrical Engineering and Computer Science, Princeton UniversityPotvrđena adresa e-pošte na princeton.edu
Ananya KumarResearch Scientist, OpenAIPotvrđena adresa e-pošte na cs.stanford.edu
Sang Michael XiePhD Candidate, Stanford UniversityPotvrđena adresa e-pošte na cs.stanford.edu
Denny ZhouResearch Scientist, Google DeepMindPotvrđena adresa e-pošte na google.com
Andrej RisteskiCarnegie Mellon UniversityPotvrđena adresa e-pošte na andrew.cmu.edu
Adrien GaidonAdjunct Professor, StanfordPotvrđena adresa e-pošte na stanford.edu
Haochen ZhangPhD Student, Stanford UniversityPotvrđena adresa e-pošte na stanford.edu
Aditi RaghunathanAssistant professor, Carnegie Mellon UniversityPotvrđena adresa e-pošte na cmu.edu
Yining ChenOpenAIPotvrđena adresa e-pošte na openai.com
Kaidi CaoStanford UniversityPotvrđena adresa e-pošte na cs.stanford.edu
Garrett ThomasStanford UniversityPotvrđena adresa e-pošte na stanford.edu
Yuping LuoComputer Science Department, Princeton UniversityPotvrđena adresa e-pošte na cs.princeton.edu
Zhiyuan LiAssistant Professor, Toyota Technological Institute at ChicagoPotvrđena adresa e-pošte na ttic.edu
Elad HazanProfessor at Princeton University and Director Google AI PrincetonPotvrđena adresa e-pošte na princeton.edu
Nikos ArechigaToyota Research InstitutePotvrđena adresa e-pošte na tri.global

Prati

Tengyu MA

Stanford University

Potvrđena adresa e-pošte na stanford.edu - Početna stranica

Machine Learning Deep Learning Theory Machine Learning Theory


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021	3808	2021
Learning imbalanced datasets with label-distribution-aware margin loss K Cao, C Wei, A Gaidon, N Arechiga, T Ma NeurIPS 2019; arXiv preprint arXiv:1906.07413, 2019	1705	2019
A simple but tough-to-beat baseline for sentence embeddings S Arora, Y Liang, T Ma ICLR 2017, 2016	1692	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	823	2017
Mopo: Model-based offline policy optimization T Yu, G Thomas, L Yu, S Ermon, JY Zou, S Levine, C Finn, T Ma Advances in Neural Information Processing Systems 33, 14129-14142, 2020	802	2020
Matrix Completion has No Spurious Local Minimum R Ge, JD Lee, T Ma NIPS 2016 (best student paper). arXiv preprint arXiv:1605.07272, 2016	718	2016
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	659*	2016
Fine-tuning can distort pretrained features and underperform out-of-distribution A Kumar, A Raghunathan, R Jones, T Ma, P Liang arXiv preprint arXiv:2202.10054, 2022	588	2022
An explanation of in-context learning as implicit bayesian inference SM Xie, A Raghunathan, P Liang, T Ma arXiv preprint arXiv:2111.02080, 2021	549	2021
Provable bounds for learning some deep representations S Arora, A Bhaskara, R Ge, T Ma International conference on machine learning, 584-592, 2014	451	2014
Identity Matters in Deep Learning M Hardt, T Ma ICLR 2017, 2016	442	2016
Fixup initialization: Residual learning without normalization H Zhang, YN Dauphin, T Ma arXiv preprint arXiv:1901.09321, 2019	380	2019
Verified uncertainty calibration A Kumar, PS Liang, T Ma Advances in Neural Information Processing Systems 32, 2019	372	2019
What learning algorithm is in-context learning? investigations with linear models E Akyürek, D Schuurmans, J Andreas, T Ma, D Zhou arXiv preprint arXiv:2211.15661, 2022	360	2022
Gradient descent learns linear dynamical systems M Hardt, T Ma, B Recht Journal of Machine Learning Research 19 (29), 1-44, 2018	354	2018
Finding Approximate Local Minima for Nonconvex Optimization in Linear Time N Agarwal, Z Allen-Zhu, B Bullins, E Hazan, T Ma STOC 2017, 2016	354*	2016
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	352*	2017
Towards explaining the regularization effect of initial large learning rate in training neural networks Y Li, C Wei, T Ma Advances in neural information processing systems 32, 2019	345	2019
Learning one-hidden-layer neural networks with landscape design R Ge, JD Lee, T Ma ICLR 2017; arXiv preprint arXiv:1711.00501, 2017	301	2017
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	286*	2019

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