Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
1810.02054
Cited By
v1
v2 (latest)
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
4 October 2018
S. Du
Xiyu Zhai
Barnabás Póczós
Aarti Singh
MLT
ODL
Re-assign community
ArXiv (abs)
PDF
HTML
Papers citing
"Gradient Descent Provably Optimizes Over-parameterized Neural Networks"
50 / 882 papers shown
Title
From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality
Fusheng Liu
Haizhao Yang
Soufiane Hayou
Qianxiao Li
AI4CE
81
2
0
22 Feb 2022
Theoretical Analysis of Deep Neural Networks in Physical Layer Communication
Jing Liu
Haitao Zhao
Dongtang Ma
Kai Mei
Jibo Wei
89
4
0
21 Feb 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks
Spencer Frei
Niladri S. Chatterji
Peter L. Bartlett
MLT
103
30
0
15 Feb 2022
Domain-Adjusted Regression or: ERM May Already Learn Features Sufficient for Out-of-Distribution Generalization
Elan Rosenfeld
Pradeep Ravikumar
Andrej Risteski
OOD
88
82
0
14 Feb 2022
Benign Overfitting in Two-layer Convolutional Neural Networks
Yuan Cao
Zixiang Chen
M. Belkin
Quanquan Gu
MLT
93
90
0
14 Feb 2022
Benign Overfitting without Linearity: Neural Network Classifiers Trained by Gradient Descent for Noisy Linear Data
Spencer Frei
Niladri S. Chatterji
Peter L. Bartlett
MLT
110
75
0
11 Feb 2022
Deep Learning in Random Neural Fields: Numerical Experiments via Neural Tangent Kernel
Kaito Watanabe
Kotaro Sakamoto
Ryo Karakida
Sho Sonoda
S. Amari
OOD
130
1
0
10 Feb 2022
Coarsening the Granularity: Towards Structurally Sparse Lottery Tickets
Tianlong Chen
Xuxi Chen
Xiaolong Ma
Yanzhi Wang
Zhangyang Wang
82
34
0
09 Feb 2022
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably
Tianyi Liu
Yan Li
Enlu Zhou
Tuo Zhao
62
1
0
07 Feb 2022
Finite-Sum Optimization: A New Perspective for Convergence to a Global Solution
Lam M. Nguyen
Trang H. Tran
Marten van Dijk
102
3
0
07 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning
Wei Huang
Chunrui Liu
Yilan Chen
Tianyu Liu
R. Xu
BDL
MLT
67
2
0
04 Feb 2022
Improved Overparametrization Bounds for Global Convergence of Stochastic Gradient Descent for Shallow Neural Networks
Bartlomiej Polaczyk
J. Cyranka
ODL
61
3
0
28 Jan 2022
Convergence of Invariant Graph Networks
Chen Cai
Yusu Wang
109
4
0
25 Jan 2022
STOPS: Short-Term-based Volatility-controlled Policy Search and its Global Convergence
Liang Xu
Daoming Lyu
Yangchen Pan
Aiwen Jiang
Bo Liu
95
0
0
24 Jan 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis
Shuai Zhang
Ming Wang
Sijia Liu
Pin-Yu Chen
Jinjun Xiong
SSL
MLT
111
23
0
21 Jan 2022
Accelerated Gradient Flow: Risk, Stability, and Implicit Regularization
Yue Sheng
Alnur Ali
122
2
0
20 Jan 2022
Learning Neural Ranking Models Online from Implicit User Feedback
Yiling Jia
Hongning Wang
94
6
0
17 Jan 2022
Towards Sample-efficient Overparameterized Meta-learning
Yue Sun
Adhyyan Narang
Halil Ibrahim Gulluk
Samet Oymak
Maryam Fazel
BDL
68
25
0
16 Jan 2022
Largest Eigenvalues of the Conjugate Kernel of Single-Layered Neural Networks
L. Benigni
Sandrine Péché
83
8
0
13 Jan 2022
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks
Benjamin Bowman
Guido Montúfar
106
11
0
12 Jan 2022
Neural calibration of hidden inhomogeneous Markov chains -- Information decompression in life insurance
Mark Kiermayer
Christian Weiß
38
0
0
07 Jan 2022
Efficient Global Optimization of Two-Layer ReLU Networks: Quadratic-Time Algorithms and Adversarial Training
Yatong Bai
Tanmay Gautam
Somayeh Sojoudi
AAML
112
17
0
06 Jan 2022
Stochastic Continuous Submodular Maximization: Boosting via Non-oblivious Function
Qixin Zhang
Zengde Deng
Zaiyi Chen
Haoyuan Hu
Yu Yang
84
20
0
03 Jan 2022
A Theoretical View of Linear Backpropagation and Its Convergence
Ziang Li
Yiwen Guo
Haodi Liu
Changshui Zhang
AAML
41
4
0
21 Dec 2021
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime
Rui Zhang
Shihua Zhang
TDI
70
23
0
15 Dec 2021
Decomposing the Deep: Finding Class Specific Filters in Deep CNNs
Akshay Badola
Cherian Roy
V. Padmanabhan
R. Lal
FAtt
64
2
0
14 Dec 2021
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time
Zhao Song
Licheng Zhang
Ruizhe Zhang
116
66
0
14 Dec 2021
SCORE: Approximating Curvature Information under Self-Concordant Regularization
Adeyemi Damilare Adeoye
Alberto Bemporad
44
4
0
14 Dec 2021
Eigenspace Restructuring: a Principle of Space and Frequency in Neural Networks
Lechao Xiao
110
22
0
10 Dec 2021
Global convergence of ResNets: From finite to infinite width using linear parameterization
Raphael Barboni
Gabriel Peyré
Franccois-Xavier Vialard
68
12
0
10 Dec 2021
Provable Continual Learning via Sketched Jacobian Approximations
Reinhard Heckel
CLL
78
10
0
09 Dec 2021
Understanding Square Loss in Training Overparametrized Neural Network Classifiers
Tianyang Hu
Jun Wang
Wei Cao
Zhenguo Li
UQCV
AAML
92
19
0
07 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao
Anastasios Kyrillidis
120
16
0
05 Dec 2021
Fast Graph Neural Tangent Kernel via Kronecker Sketching
Shunhua Jiang
Yunze Man
Zhao Song
Zheng Yu
Danyang Zhuo
96
6
0
04 Dec 2021
Pixelated Butterfly: Simple and Efficient Sparse training for Neural Network Models
Tri Dao
Beidi Chen
Kaizhao Liang
Jiaming Yang
Zhao Song
Atri Rudra
Christopher Ré
133
79
0
30 Nov 2021
Generalization Performance of Empirical Risk Minimization on Over-parameterized Deep ReLU Nets
Shao-Bo Lin
Yao Wang
Ding-Xuan Zhou
ODL
92
6
0
28 Nov 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization
Thanh Nguyen-Tang
Sunil R. Gupta
A. Nguyen
Svetha Venkatesh
OffRL
97
30
0
27 Nov 2021
KNAS: Green Neural Architecture Search
Jingjing Xu
Liang Zhao
Junyang Lin
Rundong Gao
Xu Sun
Hongxia Yang
78
59
0
26 Nov 2021
Modeling Design and Control Problems Involving Neural Network Surrogates
Dominic Yang
Prasanna Balaprakash
S. Leyffer
58
15
0
20 Nov 2021
Benchmarking and scaling of deep learning models for land cover image classification
Ioannis Papoutsis
Nikolaos Ioannis Bountos
Angelos Zavras
Dimitrios Michail
Christos Tryfonopoulos
108
61
0
18 Nov 2021
Learning with convolution and pooling operations in kernel methods
Theodor Misiakiewicz
Song Mei
MLT
90
29
0
16 Nov 2021
The Three Stages of Learning Dynamics in High-Dimensional Kernel Methods
Nikhil Ghosh
Song Mei
Bin Yu
73
20
0
13 Nov 2021
On the Equivalence between Neural Network and Support Vector Machine
Yilan Chen
Wei Huang
Lam M. Nguyen
Tsui-Wei Weng
AAML
73
18
0
11 Nov 2021
Theoretical Exploration of Flexible Transmitter Model
Jin-Hui Wu
Shao-Qun Zhang
Yuan Jiang
Zhiping Zhou
63
3
0
11 Nov 2021
Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs
Guang Lin
Christian Moya
Zecheng Zhang
76
30
0
03 Nov 2021
Subquadratic Overparameterization for Shallow Neural Networks
Chaehwan Song
Ali Ramezani-Kebrya
Thomas Pethick
Armin Eftekhari
Volkan Cevher
81
31
0
02 Nov 2021
Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias
Kaifeng Lyu
Zhiyuan Li
Runzhe Wang
Sanjeev Arora
MLT
110
76
0
26 Oct 2021
Quantifying Epistemic Uncertainty in Deep Learning
Ziyi Huang
Henry Lam
Haofeng Zhang
UQCV
BDL
UD
PER
134
14
0
23 Oct 2021
UniFed: A Unified Framework for Federated Learning on Non-IID Image Features
Meirui Jiang
Xiaoxiao Li
Xiaofei Zhang
Michael Kamp
Qianming Dou
FedML
OOD
100
0
0
19 Oct 2021
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu
Jieping Ye
Zhaoran Wang
Zhuoran Yang
OffRL
104
23
0
19 Oct 2021
Previous
1
2
3
...
7
8
9
...
16
17
18
Next