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Recovery Guarantees for One-hidden-layer Neural Networks

Recovery Guarantees for One-hidden-layer Neural Networks

10 June 2017
Kai Zhong
Zhao-quan Song
Prateek Jain
Peter L. Bartlett
Inderjit S. Dhillon
    MLT
ArXivPDFHTML

Papers citing "Recovery Guarantees for One-hidden-layer Neural Networks"

50 / 223 papers shown
Title
Learning Neural Networks with Distribution Shift: Efficiently Certifiable Guarantees
Gautam Chandrasekaran
Adam R. Klivans
Lin Lin Lee
Konstantinos Stavropoulos
OOD
40
0
0
22 Feb 2025
Event Stream-based Visual Object Tracking: HDETrack V2 and A High-Definition Benchmark
Event Stream-based Visual Object Tracking: HDETrack V2 and A High-Definition Benchmark
Shiao Wang
X. Wang
Chao wang
Liye Jin
Lin Zhu
Bo Jiang
Yonghong Tian
Jin Tang
55
0
0
08 Feb 2025
Theoretical Constraints on the Expressive Power of $\mathsf{RoPE}$-based
  Tensor Attention Transformers
Theoretical Constraints on the Expressive Power of RoPE\mathsf{RoPE}RoPE-based Tensor Attention Transformers
Xiaoyu Li
Yingyu Liang
Zhenmei Shi
Zhao-quan Song
Mingda Wan
87
8
0
23 Dec 2024
On the Hardness of Learning One Hidden Layer Neural Networks
On the Hardness of Learning One Hidden Layer Neural Networks
Shuchen Li
Ilias Zadik
Manolis Zampetakis
21
2
0
04 Oct 2024
What Improves the Generalization of Graph Transformers? A Theoretical
  Dive into the Self-attention and Positional Encoding
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding
Hongkang Li
Meng Wang
Tengfei Ma
Sijia Liu
Zaixi Zhang
Pin-Yu Chen
MLT
AI4CE
47
10
0
04 Jun 2024
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse
  Mixture-of-Experts
A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts
Mohammed Nowaz Rabbani Chowdhury
Meng Wang
K. E. Maghraoui
Naigang Wang
Pin-Yu Chen
Christopher Carothers
MoE
36
4
0
26 May 2024
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep
  Reinforcement Learning
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
Shuai Zhang
Heshan Devaka Fernando
Miao Liu
K. Murugesan
Songtao Lu
Pin-Yu Chen
Tianyi Chen
Meng Wang
44
1
0
24 May 2024
How does promoting the minority fraction affect generalization? A
  theoretical study of the one-hidden-layer neural network on group imbalance
How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance
Hongkang Li
Shuai Zhang
Yihua Zhang
Meng Wang
Sijia Liu
Pin-Yu Chen
38
4
0
12 Mar 2024
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
Early Directional Convergence in Deep Homogeneous Neural Networks for Small Initializations
Akshay Kumar
Jarvis D. Haupt
ODL
44
3
0
12 Mar 2024
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
Yingtian Zou
Kenji Kawaguchi
Yingnan Liu
Jiashuo Liu
M. Lee
W. Hsu
45
5
0
11 Mar 2024
How Do Nonlinear Transformers Learn and Generalize in In-Context
  Learning?
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Hongkang Li
Meng Wang
Songtao Lu
Xiaodong Cui
Pin-Yu Chen
MLT
42
14
0
23 Feb 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Sheng Liu
Zihan Wang
Yuxiao Chen
Qi Lei
AAML
MIACV
59
4
0
13 Feb 2024
Hidden Minima in Two-Layer ReLU Networks
Hidden Minima in Two-Layer ReLU Networks
Yossi Arjevani
32
3
0
28 Dec 2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks
  with $ε$-Greedy Exploration
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with εεε-Greedy Exploration
Shuai Zhang
Hongkang Li
Meng Wang
Miao Liu
Pin-Yu Chen
Songtao Lu
Sijia Liu
K. Murugesan
Subhajit Chaudhury
32
19
0
24 Oct 2023
An Automatic Learning Rate Schedule Algorithm for Achieving Faster
  Convergence and Steeper Descent
An Automatic Learning Rate Schedule Algorithm for Achieving Faster Convergence and Steeper Descent
Zhao-quan Song
Chiwun Yang
29
9
0
17 Oct 2023
Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets
Global Convergence of SGD For Logistic Loss on Two Layer Neural Nets
Pulkit Gopalani
Samyak Jha
Anirbit Mukherjee
16
2
0
17 Sep 2023
Max-affine regression via first-order methods
Max-affine regression via first-order methods
Seonho Kim
Kiryung Lee
25
2
0
15 Aug 2023
Efficiently Learning One-Hidden-Layer ReLU Networks via Schur
  Polynomials
Efficiently Learning One-Hidden-Layer ReLU Networks via Schur Polynomials
Ilias Diakonikolas
D. Kane
24
4
0
24 Jul 2023
A faster and simpler algorithm for learning shallow networks
A faster and simpler algorithm for learning shallow networks
Sitan Chen
Shyam Narayanan
35
7
0
24 Jul 2023
Modular Neural Network Approaches for Surgical Image Recognition
Modular Neural Network Approaches for Surgical Image Recognition
Nosseiba Ben Salem
Younès Bennani
Joseph Karkazan
Abir Barbara
Charles Dacheux
Thomas Gregory
18
0
0
17 Jul 2023
Test-Time Training on Video Streams
Test-Time Training on Video Streams
Renhao Wang
Yu Sun
Yossi Gandelsman
Xinlei Chen
Alexei A. Efros
Alexei A. Efros
Xiaolong Wang
TTA
ViT
3DGS
37
16
0
11 Jul 2023
Fast, Distribution-free Predictive Inference for Neural Networks with
  Coverage Guarantees
Fast, Distribution-free Predictive Inference for Neural Networks with Coverage Guarantees
Yue Gao
Garvesh Raskutti
Rebecca Willett
27
0
0
11 Jun 2023
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural
  Language Understanding
InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding
Junda Wu
Tong Yu
Rui Wang
Zhao-quan Song
Ruiyi Zhang
Handong Zhao
Chaochao Lu
Shuai Li
Ricardo Henao
VLM
31
22
0
08 Jun 2023
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient
  for Convolutional Neural Networks
Patch-level Routing in Mixture-of-Experts is Provably Sample-efficient for Convolutional Neural Networks
Mohammed Nowaz Rabbani Chowdhury
Shuai Zhang
M. Wang
Sijia Liu
Pin-Yu Chen
MoE
29
17
0
07 Jun 2023
Most Neural Networks Are Almost Learnable
Most Neural Networks Are Almost Learnable
Amit Daniely
Nathan Srebro
Gal Vardi
20
0
0
25 May 2023
Toward $L_\infty$-recovery of Nonlinear Functions: A Polynomial Sample
  Complexity Bound for Gaussian Random Fields
Toward L∞L_\inftyL∞​-recovery of Nonlinear Functions: A Polynomial Sample Complexity Bound for Gaussian Random Fields
Kefan Dong
Tengyu Ma
35
4
0
29 Apr 2023
Expand-and-Cluster: Parameter Recovery of Neural Networks
Expand-and-Cluster: Parameter Recovery of Neural Networks
Flavio Martinelli
Berfin Simsek
W. Gerstner
Johanni Brea
26
4
0
25 Apr 2023
Learning Narrow One-Hidden-Layer ReLU Networks
Learning Narrow One-Hidden-Layer ReLU Networks
Sitan Chen
Zehao Dou
Surbhi Goel
Adam R. Klivans
Raghu Meka
MLT
19
13
0
20 Apr 2023
DiffFit: Unlocking Transferability of Large Diffusion Models via Simple
  Parameter-Efficient Fine-Tuning
DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning
Enze Xie
Lewei Yao
Han Shi
Zhili Liu
Daquan Zhou
Zhaoqiang Liu
Jiawei Li
Zhenguo Li
26
76
0
13 Apr 2023
Over-Parameterization Exponentially Slows Down Gradient Descent for
  Learning a Single Neuron
Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron
Weihang Xu
S. Du
29
16
0
20 Feb 2023
Computational Complexity of Learning Neural Networks: Smoothness and
  Degeneracy
Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy
Amit Daniely
Nathan Srebro
Gal Vardi
25
4
0
15 Feb 2023
A Theoretical Understanding of Shallow Vision Transformers: Learning,
  Generalization, and Sample Complexity
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity
Hongkang Li
M. Wang
Sijia Liu
Pin-Yu Chen
ViT
MLT
37
57
0
12 Feb 2023
Generalization Ability of Wide Neural Networks on $\mathbb{R}$
Generalization Ability of Wide Neural Networks on R\mathbb{R}R
Jianfa Lai
Manyun Xu
Rui Chen
Qi-Rong Lin
26
21
0
12 Feb 2023
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural
  Networks
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
Shuai Zhang
M. Wang
Pin-Yu Chen
Sijia Liu
Songtao Lu
Miaoyuan Liu
MLT
19
16
0
06 Feb 2023
Reconstructing Training Data from Model Gradient, Provably
Reconstructing Training Data from Model Gradient, Provably
Zihan Wang
Jason D. Lee
Qi Lei
FedML
22
24
0
07 Dec 2022
Finite Sample Identification of Wide Shallow Neural Networks with Biases
Finite Sample Identification of Wide Shallow Neural Networks with Biases
M. Fornasier
T. Klock
Marco Mondelli
Michael Rauchensteiner
19
6
0
08 Nov 2022
Learning Single-Index Models with Shallow Neural Networks
Learning Single-Index Models with Shallow Neural Networks
A. Bietti
Joan Bruna
Clayton Sanford
M. Song
164
67
0
27 Oct 2022
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
Bures-Wasserstein Barycenters and Low-Rank Matrix Recovery
Tyler Maunu
Thibaut Le Gouic
Philippe Rigollet
20
5
0
26 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets
Global Convergence of SGD On Two Layer Neural Nets
Pulkit Gopalani
Anirbit Mukherjee
23
5
0
20 Oct 2022
Annihilation of Spurious Minima in Two-Layer ReLU Networks
Annihilation of Spurious Minima in Two-Layer ReLU Networks
Yossi Arjevani
M. Field
16
8
0
12 Oct 2022
Neural Networks Efficiently Learn Low-Dimensional Representations with
  SGD
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD
Alireza Mousavi-Hosseini
Sejun Park
M. Girotti
Ioannis Mitliagkas
Murat A. Erdogdu
MLT
324
48
0
29 Sep 2022
Is Stochastic Gradient Descent Near Optimal?
Is Stochastic Gradient Descent Near Optimal?
Yifan Zhu
Hong Jun Jeon
Benjamin Van Roy
21
2
0
18 Sep 2022
Agnostic Learning of General ReLU Activation Using Gradient Descent
Agnostic Learning of General ReLU Activation Using Gradient Descent
Pranjal Awasthi
Alex K. Tang
Aravindan Vijayaraghavan
MLT
10
7
0
04 Aug 2022
Learning and generalization of one-hidden-layer neural networks, going
  beyond standard Gaussian data
Learning and generalization of one-hidden-layer neural networks, going beyond standard Gaussian data
Hongkang Li
Shuai Zhang
M. Wang
MLT
8
8
0
07 Jul 2022
Generalization Guarantee of Training Graph Convolutional Networks with
  Graph Topology Sampling
Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling
Hongkang Li
M. Wang
Sijia Liu
Pin-Yu Chen
Jinjun Xiong
GNN
16
27
0
07 Jul 2022
Bounding the Width of Neural Networks via Coupled Initialization -- A
  Worst Case Analysis
Bounding the Width of Neural Networks via Coupled Initialization -- A Worst Case Analysis
Alexander Munteanu
Simon Omlor
Zhao-quan Song
David P. Woodruff
27
15
0
26 Jun 2022
Local Identifiability of Deep ReLU Neural Networks: the Theory
Local Identifiability of Deep ReLU Neural Networks: the Theory
Joachim Bona-Pellissier
Franccois Malgouyres
F. Bachoc
FAtt
67
6
0
15 Jun 2022
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student
  Settings and its Superiority to Kernel Methods
Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods
Shunta Akiyama
Taiji Suzuki
30
6
0
30 May 2022
The Mechanism of Prediction Head in Non-contrastive Self-supervised
  Learning
The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning
Zixin Wen
Yuanzhi Li
SSL
27
34
0
12 May 2022
An Information-Theoretic Framework for Supervised Learning
An Information-Theoretic Framework for Supervised Learning
Hong Jun Jeon
Yifan Zhu
Benjamin Van Roy
22
7
0
01 Mar 2022
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