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1905.13210
Cited By
Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
30 May 2019
Yuan Cao
Quanquan Gu
MLT
AI4CE
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Papers citing
"Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks"
50 / 120 papers shown
Title
Benefit of Interpolation in Nearest Neighbor Algorithms
Yue Xing
Qifan Song
Guang Cheng
14
28
0
23 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning
Wei Huang
Chunrui Liu
Yilan Chen
Tianyu Liu
R. Xu
BDL
MLT
19
2
0
04 Feb 2022
Deep Layer-wise Networks Have Closed-Form Weights
Chieh-Tsai Wu
A. Masoomi
Arthur Gretton
Jennifer Dy
29
3
0
01 Feb 2022
Neural Collaborative Filtering Bandits via Meta Learning
Yikun Ban
Yunzhe Qi
Tianxin Wei
Jingrui He
OffRL
33
9
0
31 Jan 2022
Interplay between depth of neural networks and locality of target functions
Takashi Mori
Masakuni Ueda
25
0
0
28 Jan 2022
Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces
Hao Liu
Haizhao Yang
Minshuo Chen
T. Zhao
Wenjing Liao
32
36
0
01 Jan 2022
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime
Rui Zhang
Shihua Zhang
TDI
27
21
0
15 Dec 2021
Training Multi-Layer Over-Parametrized Neural Network in Subquadratic Time
Zhao Song
Licheng Zhang
Ruizhe Zhang
32
64
0
14 Dec 2021
Non-Asymptotic Analysis of Online Multiplicative Stochastic Gradient Descent
Riddhiman Bhattacharya
Tiefeng Jiang
16
0
0
14 Dec 2021
Understanding Square Loss in Training Overparametrized Neural Network Classifiers
Tianyang Hu
Jun Wang
Wei Cao
Zhenguo Li
UQCV
AAML
41
19
0
07 Dec 2021
Offline Neural Contextual Bandits: Pessimism, Optimization and Generalization
Thanh Nguyen-Tang
Sunil R. Gupta
A. Nguyen
Svetha Venkatesh
OffRL
29
29
0
27 Nov 2021
On the Equivalence between Neural Network and Support Vector Machine
Yilan Chen
Wei Huang
Lam M. Nguyen
Tsui-Wei Weng
AAML
25
18
0
11 Nov 2021
Quantifying Epistemic Uncertainty in Deep Learning
Ziyi Huang
H. Lam
Haofeng Zhang
UQCV
BDL
UD
PER
24
12
0
23 Oct 2021
Deep Active Learning by Leveraging Training Dynamics
Haonan Wang
Wei Huang
Ziwei Wu
A. Margenot
Hanghang Tong
Jingrui He
AI4CE
27
33
0
16 Oct 2021
Provable Regret Bounds for Deep Online Learning and Control
Xinyi Chen
Edgar Minasyan
Jason D. Lee
Elad Hazan
36
6
0
15 Oct 2021
Does Preprocessing Help Training Over-parameterized Neural Networks?
Zhao Song
Shuo Yang
Ruizhe Zhang
38
49
0
09 Oct 2021
EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits
Yikun Ban
Yuchen Yan
A. Banerjee
Jingrui He
OffRL
37
39
0
07 Oct 2021
The Role of Lookahead and Approximate Policy Evaluation in Reinforcement Learning with Linear Value Function Approximation
Anna Winnicki
Joseph Lubars
Michael Livesay
R. Srikant
31
3
0
28 Sep 2021
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization
Difan Zou
Yuan Cao
Yuanzhi Li
Quanquan Gu
MLT
AI4CE
47
39
0
25 Aug 2021
Towards General Function Approximation in Zero-Sum Markov Games
Baihe Huang
Jason D. Lee
Zhaoran Wang
Zhuoran Yang
33
47
0
30 Jul 2021
Deep Networks Provably Classify Data on Curves
Tingran Wang
Sam Buchanan
D. Gilboa
John N. Wright
23
9
0
29 Jul 2021
The Values Encoded in Machine Learning Research
Abeba Birhane
Pratyusha Kalluri
Dallas Card
William Agnew
Ravit Dotan
Michelle Bao
41
274
0
29 Jun 2021
The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective
Geoff Pleiss
John P. Cunningham
28
24
0
11 Jun 2021
Neural Active Learning with Performance Guarantees
Pranjal Awasthi
Christoph Dann
Claudio Gentile
Ayush Sekhari
Zhilei Wang
29
22
0
06 Jun 2021
Generalization Guarantees for Neural Architecture Search with Train-Validation Split
Samet Oymak
Mingchen Li
Mahdi Soltanolkotabi
AI4CE
OOD
36
13
0
29 Apr 2021
Reframing Neural Networks: Deep Structure in Overcomplete Representations
Calvin Murdock
George Cazenavette
Simon Lucey
BDL
41
4
0
10 Mar 2021
A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network
Mo Zhou
Rong Ge
Chi Jin
76
45
0
04 Feb 2021
A Convergence Theory Towards Practical Over-parameterized Deep Neural Networks
Asaf Noy
Yi Tian Xu
Y. Aflalo
Lihi Zelnik-Manor
Rong Jin
41
3
0
12 Jan 2021
Provable Generalization of SGD-trained Neural Networks of Any Width in the Presence of Adversarial Label Noise
Spencer Frei
Yuan Cao
Quanquan Gu
FedML
MLT
70
19
0
04 Jan 2021
Advances in Electron Microscopy with Deep Learning
Jeffrey M. Ede
37
2
0
04 Jan 2021
Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning
Zeyuan Allen-Zhu
Yuanzhi Li
FedML
60
356
0
17 Dec 2020
Gradient Starvation: A Learning Proclivity in Neural Networks
Mohammad Pezeshki
Sekouba Kaba
Yoshua Bengio
Aaron Courville
Doina Precup
Guillaume Lajoie
MLT
50
258
0
18 Nov 2020
On Function Approximation in Reinforcement Learning: Optimism in the Face of Large State Spaces
Zhuoran Yang
Chi Jin
Zhaoran Wang
Mengdi Wang
Michael I. Jordan
39
18
0
09 Nov 2020
Deep Learning is Singular, and That's Good
Daniel Murfet
Susan Wei
Biwei Huang
Hui Li
Jesse Gell-Redman
T. Quella
UQCV
24
26
0
22 Oct 2020
Knowledge Distillation in Wide Neural Networks: Risk Bound, Data Efficiency and Imperfect Teacher
Guangda Ji
Zhanxing Zhu
59
42
0
20 Oct 2020
For self-supervised learning, Rationality implies generalization, provably
Yamini Bansal
Gal Kaplun
Boaz Barak
OOD
SSL
58
22
0
16 Oct 2020
Neural Thompson Sampling
Weitong Zhang
Dongruo Zhou
Lihong Li
Quanquan Gu
34
115
0
02 Oct 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks
Keyulu Xu
Mozhi Zhang
Jingling Li
S. Du
Ken-ichi Kawarabayashi
Stefanie Jegelka
MLT
25
306
0
24 Sep 2020
Deep Neural Tangent Kernel and Laplace Kernel Have the Same RKHS
Lin Chen
Sheng Xu
32
93
0
22 Sep 2020
Review: Deep Learning in Electron Microscopy
Jeffrey M. Ede
36
79
0
17 Sep 2020
Deep Networks and the Multiple Manifold Problem
Sam Buchanan
D. Gilboa
John N. Wright
166
39
0
25 Aug 2020
Obtaining Adjustable Regularization for Free via Iterate Averaging
Jingfeng Wu
Vladimir Braverman
Lin F. Yang
30
2
0
15 Aug 2020
Multiple Descent: Design Your Own Generalization Curve
Lin Chen
Yifei Min
M. Belkin
Amin Karbasi
DRL
33
61
0
03 Aug 2020
Single-Timescale Actor-Critic Provably Finds Globally Optimal Policy
Zuyue Fu
Zhuoran Yang
Zhaoran Wang
18
42
0
02 Aug 2020
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training
Andrea Montanari
Yiqiao Zhong
49
95
0
25 Jul 2020
Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy
E. Moroshko
Suriya Gunasekar
Blake E. Woodworth
J. Lee
Nathan Srebro
Daniel Soudry
35
85
0
13 Jul 2020
Associative Memory in Iterated Overparameterized Sigmoid Autoencoders
Yibo Jiang
Cengiz Pehlevan
19
13
0
30 Jun 2020
Two-Layer Neural Networks for Partial Differential Equations: Optimization and Generalization Theory
Tao Luo
Haizhao Yang
32
74
0
28 Jun 2020
Training (Overparametrized) Neural Networks in Near-Linear Time
Jan van den Brand
Binghui Peng
Zhao Song
Omri Weinstein
ODL
29
82
0
20 Jun 2020
Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory
Yufeng Zhang
Qi Cai
Zhuoran Yang
Yongxin Chen
Zhaoran Wang
OOD
MLT
138
11
0
08 Jun 2020
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