Rong Ge
Cited by
Cited by
Tensor decompositions for learning latent variable models.
A Anandkumar, R Ge, DJ Hsu, SM Kakade, M Telgarsky
J. Mach. Learn. Res. 15 (1), 2773-2832, 2014
Escaping from saddle points—online stochastic gradient for tensor decomposition
R Ge, F Huang, C Jin, Y Yuan
Conference on learning theory, 797-842, 2015
How to escape saddle points efficiently
C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan
International conference on machine learning, 1724-1732, 2017
Generalization and equilibrium in generative adversarial nets (gans)
S Arora, R Ge, Y Liang, T Ma, Y Zhang
International conference on machine learning, 224-232, 2017
Matrix completion has no spurious local minimum
R Ge, JD Lee, T Ma
Advances in neural information processing systems 29, 2016
Global convergence of policy gradient methods for the linear quadratic regulator
M Fazel, R Ge, S Kakade, M Mesbahi
International conference on machine learning, 1467-1476, 2018
Stronger generalization bounds for deep nets via a compression approach
S Arora, R Ge, B Neyshabur, Y Zhang
International Conference on Machine Learning, 254-263, 2018
A practical algorithm for topic modeling with provable guarantees
S Arora, R Ge, Y Halpern, D Mimno, A Moitra, D Sontag, Y Wu, M Zhu
International conference on machine learning, 280-288, 2013
Learning topic models--going beyond SVD
S Arora, R Ge, A Moitra
2012 IEEE 53rd annual symposium on foundations of computer science, 1-10, 2012
Computing a nonnegative matrix factorization--provably
S Arora, R Ge, R Kannan, A Moitra
Proceedings of the forty-fourth annual ACM symposium on Theory of computing …, 2012
No spurious local minima in nonconvex low rank problems: A unified geometric analysis
R Ge, C Jin, Y Zheng
International Conference on Machine Learning, 1233-1242, 2017
Provable bounds for learning some deep representations
S Arora, A Bhaskara, R Ge, T Ma
International conference on machine learning, 584-592, 2014
New algorithms for learning in presence of errors
S Arora, R Ge
Automata, Languages and Programming, 403-415, 2011
Learning one-hidden-layer neural networks with landscape design
R Ge, JD Lee, T Ma
arXiv preprint arXiv:1711.00501, 2017
New algorithms for learning incoherent and overcomplete dictionaries
S Arora, R Ge, A Moitra
Conference on Learning Theory, 779-806, 2014
Simple, efficient, and neural algorithms for sparse coding
S Arora, R Ge, T Ma, A Moitra
Conference on learning theory, 113-149, 2015
Computational complexity and information asymmetry in financial products
S Arora, B Barak, M Brunnermeier, R Ge
Communications of the ACM 54 (5), 101-107, 2011
A tensor approach to learning mixed membership community models
A Anandkumar, R Ge, D Hsu, SM Kakade
The Journal of Machine Learning Research 15 (1), 2239-2312, 2014
On nonconvex optimization for machine learning: Gradients, stochasticity, and saddle points
C Jin, P Netrapalli, R Ge, SM Kakade, MI Jordan
Journal of the ACM (JACM) 68 (2), 1-29, 2021
Efficient approaches for escaping higher order saddle points in non-convex optimization
A Anandkumar, R Ge
Conference on learning theory, 81-102, 2016
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