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A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
4 October 2018
Sanjeev Arora
Nadav Cohen
Noah Golowich
Wei Hu
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Papers citing
"A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks"
10 / 210 papers shown
Depth creates no more spurious local minima
Li Zhang
226
19
0
28 Jan 2019
Width Provably Matters in Optimization for Deep Linear Neural Networks
S. Du
Wei Hu
386
101
0
24 Jan 2019
On Connected Sublevel Sets in Deep Learning
Quynh N. Nguyen
275
106
0
22 Jan 2019
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks
Difan Zou
Yuan Cao
Dongruo Zhou
Quanquan Gu
ODL
515
452
0
21 Nov 2018
Effect of Depth and Width on Local Minima in Deep Learning
Neural Computation (Neural Comput.), 2018
Kenji Kawaguchi
Jiaoyang Huang
L. Kaelbling
231
58
0
20 Nov 2018
A Convergence Theory for Deep Learning via Over-Parameterization
International Conference on Machine Learning (ICML), 2018
Zeyuan Allen-Zhu
Yuanzhi Li
Zhao Song
AI4CE
ODL
1.4K
1,555
0
09 Nov 2018
On the Convergence Rate of Training Recurrent Neural Networks
Zeyuan Allen-Zhu
Yuanzhi Li
Zhao Song
574
199
0
29 Oct 2018
Exponential Convergence Time of Gradient Descent for One-Dimensional Deep Linear Neural Networks
Ohad Shamir
181
48
0
23 Sep 2018
Collapse of Deep and Narrow Neural Nets
Lu Lu
Yanhui Su
George Karniadakis
ODL
233
164
0
15 Aug 2018
QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
Tabish Rashid
Mikayel Samvelyan
Christian Schroeder de Witt
Gregory Farquhar
Jakob N. Foerster
Shimon Whiteson
519
1,866
0
30 Mar 2018
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