Cong Fang
Cong Fang
Princeton
Verified email at pku.edu.cn
Title
Cited by
Cited by
Year
Spider: Near-optimal non-convex optimization via stochastic path-integrated differential estimator
C Fang, CJ Li, Z Lin, T Zhang
Advances in Neural Information Processing Systems, 689-699, 2018
1642018
Sharp analysis for nonconvex sgd escaping from saddle points
C Fang, Z Lin, T Zhang
arXiv preprint arXiv:1902.00247, 2019
312019
A robust hybrid method for text detection in natural scenes by learning-based partial differential equations
Z Zhao, C Fang, Z Lin, Y Wu
Neurocomputing 168, 23-34, 2015
242015
Complexities in projection-free stochastic non-convex minimization
Z Shen, C Fang, P Zhao, J Huang, H Qian
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
162019
A sharp convergence rate analysis for distributed accelerated gradient methods
H Li, C Fang, W Yin, Z Lin
arXiv preprint arXiv:1810.01053, 2018
162018
Feature learning via partial differential equation with applications to face recognition
C Fang, Z Zhao, P Zhou, Z Lin
Pattern Recognition 69, 14-25, 2017
132017
Dictionary learning with structured noise
P Zhou, C Fang, Z Lin, C Zhang, EY Chang
Neurocomputing 273, 414-423, 2018
112018
Lifted proximal operator machines
J Li, C Fang, Z Lin
Proceedings of the AAAI Conference on Artificial Intelligence 33, 4181-4188, 2019
102019
Hessian-aware zeroth-order optimization for black-box adversarial attack
H Ye, Z Huang, C Fang, CJ Li, T Zhang
arXiv preprint arXiv:1812.11377, 2018
92018
Over parameterized two-level neural networks can learn near optimal feature representations
C Fang, H Dong, T Zhang
arXiv preprint arXiv:1910.11508, 2019
72019
Parallel asynchronous stochastic variance reduction for nonconvex optimization
C Fang, Z Lin
Thirty-First AAAI Conference on Artificial Intelligence, 2017
72017
Faster and non-ergodic O (1/k) stochastic alternating direction method of multipliers
C Fang, F Cheng, Z Lin
Advances in Neural Information Processing Systems, 4476-4485, 2017
62017
Convex formulation of overparameterized deep neural networks
C Fang, Y Gu, W Zhang, T Zhang
arXiv preprint arXiv:1911.07626, 2019
52019
Accelerating asynchronous algorithms for convex optimization by momentum compensation
C Fang, Y Huang, Z Lin
arXiv preprint arXiv:1802.09747, 2018
52018
A stochastic trust region method for non-convex minimization
Z Shen, P Zhou, C Fang, A Ribeiro
arXiv preprint arXiv:1903.01540, 2019
32019
Convergence rates analysis of the quadratic penalty method and its applications to decentralized distributed optimization
H Li, C Fang, Z Lin
arXiv preprint arXiv:1711.10802, 2017
32017
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks
C Fang, JD Lee, P Yang, T Zhang
arXiv preprint arXiv:2007.01452, 2020
22020
Decentralized Accelerated Gradient Methods With Increasing Penalty Parameters
H Li, C Fang, W Yin, Z Lin
IEEE Transactions on Signal Processing 68, 4855-4870, 2020
12020
Learning Compact Partial Differential Equations for Color Images with Efficiency
Z Zhao, C Hou, B Lin, C Fang
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
12019
Improved Analysis of Clipping Algorithms for Non-convex Optimization
B Zhang, J Jin, C Fang, L Wang
arXiv preprint arXiv:2010.02519, 2020
2020
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