Jason D. Lee

Получаване на мой собствен потребителски профил

Позовавания

	Всички	От 2019
Позовавания	18981	16769
h-индекс	64	61
i10-индекс	126	125

4300

2150

1075

3225

20132014201520162017201820192020202120222023202455 107 166 283 534 904 1560 2075 2615 2888 3391 4216

Публичен достъп

Преглед на всички

62 статии

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Въз основа на изисквания при финансирането

Съавтори

Simon Shaolei DuAssistant Professor, School of Computer Science and Engineering, University of WashingtonПотвърден имейл адрес: cs.washington.edu
Yuekai SunUniversity of MichiganПотвърден имейл адрес: umich.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyПотвърден имейл адрес: cs.berkeley.edu
Sham M KakadeHarvard UniversityПотвърден имейл адрес: seas.harvard.edu
Qi LeiAssistant Professor of Mathematics and Data Science, New York UniversityПотвърден имейл адрес: nyu.edu
Tengyu MAStanford UniversityПотвърден имейл адрес: stanford.edu
Nathan SrebroProfessor, TTIC and University of ChicagoПотвърден имейл адрес: ttic.edu
Wenhao ZhanGraduate Student, Princeton UniversityПотвърден имейл адрес: princeton.edu
Jonathan TaylorProfessor of Statistics, Stanford UniversityПотвърден имейл адрес: stanford.edu
Wen SunAssistant Professor, Cornell UniversityПотвърден имейл адрес: cornell.edu
Suriya GunasekarMSR RedmondПотвърден имейл адрес: ttic.edu
Daniel SoudryAssociate ProfessorПотвърден имейл адрес: technion.ac.il
Qiang LiuAssociate Professor of Computer Science, UT AustinПотвърден имейл адрес: cs.utexas.edu
Haochuan LiMIT EECSПотвърден имейл адрес: mit.edu
Alex DamianPh.D. Student, Princeton UniversityПотвърден имейл адрес: princeton.edu
Gaurav MahajanPostdoctoral Associate, Yale UniversityПотвърден имейл адрес: yale.edu
Tianle CaiPhD Student, Princeton UniversityПотвърден имейл адрес: princeton.edu
Liwei WangProfessor, Peking UniversityПотвърден имейл адрес: cis.pku.edu.cn
Rong GeDuke UniversityПотвърден имейл адрес: cs.duke.edu
Benjamin RechtProfessor of EECS, University of California, BerkeleyПотвърден имейл адрес: eecs.berkeley.edu

Следене

Jason D. Lee

Други именаJason Lee

Associate Professor of Electrical Engineering and Computer Science, Princeton University

Потвърден имейл адрес: princeton.edu - Начална страница

Machine Learning Theory Machine Learning Artificial Intelligence Statistics Optimization


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
Gradient descent finds global minima of deep neural networks SS Du, JD Lee, H Li, L Wang, X Zhai arXiv preprint arXiv:1811.03804, 2018	1400	2018
Exact post-selection inference, with application to the lasso JD Lee, DL Sun, Y Sun, JE Taylor The Annals of Statistics 44 (3), 907-927, 2016	993	2016
Gradient descent only converges to minimizers JD Lee, M Simchowitz, MI Jordan, B Recht Conference on learning theory, 1246-1257, 2016	909*	2016
On the theory of policy gradient methods: Optimality, approximation, and distribution shift A Agarwal, SM Kakade, JD Lee, G Mahajan Journal of Machine Learning Research 22 (98), 1-76, 2021	848*	2021
Matrix completion has no spurious local minimum R Ge, JD Lee, T Ma Advances in neural information processing systems 29, 2016	730	2016
Matrix completion and low-rank SVD via fast alternating least squares T Hastie, R Mazumder, J Lee, R Zadeh Journal of Machine Learning Research, 2014	648	2014
A kernelized Stein discrepancy for goodness-of-fit tests Q Liu, J Lee, M Jordan International conference on machine learning, 276-284, 2016	548	2016
Communication-efficient distributed statistical inference MI Jordan, JD Lee, Y Yang Journal of the American Statistical Association, 2019	495	2019
Theoretical insights into the optimization landscape of over-parameterized shallow neural networks M Soltanolkotabi, A Javanmard, JD Lee IEEE Transactions on Information Theory 65 (2), 742-769, 2018	480	2018
Proximal Newton-type methods for minimizing composite functions JD Lee, Y Sun, MA Saunders SIAM Journal on Optimization 24 (3), 1420-1443, 2014	479*	2014
Characterizing implicit bias in terms of optimization geometry S Gunasekar, J Lee, D Soudry, N Srebro International Conference on Machine Learning, 1832-1841, 2018	477	2018
Implicit bias of gradient descent on linear convolutional networks S Gunasekar, JD Lee, D Soudry, N Srebro Advances in neural information processing systems 31, 2018	465	2018
Solving a class of non-convex min-max games using iterative first order methods M Nouiehed, M Sanjabi, T Huang, JD Lee, M Razaviyayn Advances in Neural Information Processing Systems 32, 2019	395	2019
Kernel and rich regimes in overparametrized models B Woodworth, S Gunasekar, JD Lee, E Moroshko, P Savarese, I Golan, ... Conference on Learning Theory, 3635-3673, 2020	392	2020
First-order methods almost always avoid strict saddle points JD Lee, I Panageas, G Piliouras, M Simchowitz, MI Jordan, B Recht Mathematical programming 176 (1-2), 311-337, 2019	378	2019
Learning one-hidden-layer neural networks with landscape design R Ge, JD Lee, T Ma arXiv preprint arXiv:1711.00501, 2017	309	2017
Gradient descent can take exponential time to escape saddle points SS Du, C Jin, JD Lee, MI Jordan, A Singh, B Poczos Advances in neural information processing systems 30, 2017	307	2017
On the power of over-parametrization in neural networks with quadratic activation S Du, J Lee International conference on machine learning, 1329-1338, 2018	291	2018
Few-shot learning via learning the representation, provably SS Du, W Hu, SM Kakade, JD Lee, Q Lei arXiv preprint arXiv:2002.09434, 2020	284	2020
Stochastic subgradient method converges on tame functions D Davis, D Drusvyatskiy, S Kakade, JD Lee Foundations of computational mathematics 20 (1), 119-154, 2020	281	2020

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