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On Exact Computation with an Infinitely Wide Neural Net

On Exact Computation with an Infinitely Wide Neural Net

26 April 2019
Sanjeev Arora
S. Du
Wei Hu
Zhiyuan Li
Ruslan Salakhutdinov
Ruosong Wang
ArXivPDFHTML

Papers citing "On Exact Computation with an Infinitely Wide Neural Net"

50 / 266 papers shown
Title
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
Francesco Camilli
D. Tieplova
Eleonora Bergamin
Jean Barbier
192
0
0
06 May 2025
Don't be lazy: CompleteP enables compute-efficient deep transformers
Don't be lazy: CompleteP enables compute-efficient deep transformers
Nolan Dey
Bin Claire Zhang
Lorenzo Noci
Mufan Li
Blake Bordelon
Shane Bergsma
Cengiz Pehlevan
Boris Hanin
Joel Hestness
44
1
0
02 May 2025
Deep learning with missing data
Deep learning with missing data
Tianyi Ma
Tengyao Wang
R. Samworth
69
0
0
21 Apr 2025
Generalization through variance: how noise shapes inductive biases in diffusion models
Generalization through variance: how noise shapes inductive biases in diffusion models
John J. Vastola
DiffM
242
2
0
16 Apr 2025
On the Cone Effect in the Learning Dynamics
On the Cone Effect in the Learning Dynamics
Zhanpeng Zhou
Yongyi Yang
Jie Ren
Mahito Sugiyama
Junchi Yan
53
0
0
20 Mar 2025
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong
Kecen Li
Zinan Lin
Tianhao Wang
64
3
0
18 Mar 2025
FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning
FACTR: Force-Attending Curriculum Training for Contact-Rich Policy Learning
Jason Jingzhou Liu
Yulong Li
Kenneth Shaw
Tony Tao
Ruslan Salakhutdinov
Deepak Pathak
OffRL
67
1
0
24 Feb 2025
Learn Sharp Interface Solution by Homotopy Dynamics
Learn Sharp Interface Solution by Homotopy Dynamics
Chuqi Chen
Yahong Yang
Yang Xiang
Wenrui Hao
ODL
65
1
0
01 Feb 2025
Issues with Neural Tangent Kernel Approach to Neural Networks
Issues with Neural Tangent Kernel Approach to Neural Networks
Haoran Liu
Anthony S. Tai
David J. Crandall
Chunfeng Huang
42
0
0
19 Jan 2025
An Analysis Framework for Understanding Deep Neural Networks Based on Network Dynamics
An Analysis Framework for Understanding Deep Neural Networks Based on Network Dynamics
Yuchen Lin
Yong Zhang
Sihan Feng
Hong Zhao
41
0
0
05 Jan 2025
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits
H. Bui
Enrique Mallada
Anqi Liu
192
0
0
08 Nov 2024
On the Impacts of the Random Initialization in the Neural Tangent Kernel
  Theory
On the Impacts of the Random Initialization in the Neural Tangent Kernel Theory
Guhan Chen
Yicheng Li
Qian Lin
AAML
40
1
0
08 Oct 2024
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks
Clémentine Dominé
Nicolas Anguita
A. Proca
Lukas Braun
D. Kunin
P. Mediano
Andrew M. Saxe
40
3
0
22 Sep 2024
Re-evaluating the Advancements of Heterophilic Graph Learning
Re-evaluating the Advancements of Heterophilic Graph Learning
Sitao Luan
Qincheng Lu
Chenqing Hua
Xinyu Wang
Jiaqi Zhu
Xiao-Wen Chang
70
2
0
09 Sep 2024
Graph Neural Thompson Sampling
Graph Neural Thompson Sampling
Shuang Wu
Arash A. Amini
53
0
0
15 Jun 2024
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees
A. Banerjee
Qiaobo Li
Yingxue Zhou
52
0
0
11 Jun 2024
Equivariant Neural Tangent Kernels
Equivariant Neural Tangent Kernels
Philipp Misof
Pan Kessel
Jan E. Gerken
64
0
0
10 Jun 2024
Thermodynamic limit in learning period three
Thermodynamic limit in learning period three
Yuichiro Terasaki
Kohei Nakajima
42
1
0
12 May 2024
Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks
Regularized Gradient Clipping Provably Trains Wide and Deep Neural Networks
Matteo Tucat
Anirbit Mukherjee
Procheta Sen
Mingfei Sun
Omar Rivasplata
MLT
39
1
0
12 Apr 2024
Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization
Implicit Bias of AdamW: ℓ∞\ell_\inftyℓ∞​ Norm Constrained Optimization
Shuo Xie
Zhiyuan Li
OffRL
50
13
0
05 Apr 2024
Anytime Neural Architecture Search on Tabular Data
Anytime Neural Architecture Search on Tabular Data
Naili Xing
Shaofeng Cai
Zhaojing Luo
Bengchin Ooi
Jian Pei
36
1
0
15 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 Haupt
ODL
46
3
0
12 Mar 2024
Improve Generalization Ability of Deep Wide Residual Network with A
  Suitable Scaling Factor
Improve Generalization Ability of Deep Wide Residual Network with A Suitable Scaling Factor
Songtao Tian
Zixiong Yu
32
1
0
07 Mar 2024
Active Few-Shot Fine-Tuning
Active Few-Shot Fine-Tuning
Jonas Hübotter
Bhavya Sukhija
Lenart Treven
Yarden As
Andreas Krause
48
1
0
13 Feb 2024
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning
Yuxiao Wen
Arthur Jacot
65
6
0
12 Feb 2024
Weak Correlations as the Underlying Principle for Linearization of
  Gradient-Based Learning Systems
Weak Correlations as the Underlying Principle for Linearization of Gradient-Based Learning Systems
Ori Shem-Ur
Yaron Oz
21
0
0
08 Jan 2024
Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning
  Based on Gaussian Moments
Thermally Averaged Magnetic Anisotropy Tensors via Machine Learning Based on Gaussian Moments
Viktor Zaverkin
Julia Netz
Fabian Zills
Andreas Köhn
Johannes Kastner
AI4CE
32
16
0
03 Dec 2023
A qualitative difference between gradient flows of convex functions in
  finite- and infinite-dimensional Hilbert spaces
A qualitative difference between gradient flows of convex functions in finite- and infinite-dimensional Hilbert spaces
Jonathan W. Siegel
Stephan Wojtowytsch
21
3
0
26 Oct 2023
On the Neural Tangent Kernel of Equilibrium Models
On the Neural Tangent Kernel of Equilibrium Models
Zhili Feng
J. Zico Kolter
20
6
0
21 Oct 2023
Differentially Private Non-convex Learning for Multi-layer Neural
  Networks
Differentially Private Non-convex Learning for Multi-layer Neural Networks
Hanpu Shen
Cheng-Long Wang
Zihang Xiang
Yiming Ying
Di Wang
51
7
0
12 Oct 2023
How to Protect Copyright Data in Optimization of Large Language Models?
How to Protect Copyright Data in Optimization of Large Language Models?
T. Chu
Zhao Song
Chiwun Yang
45
29
0
23 Aug 2023
Modify Training Directions in Function Space to Reduce Generalization
  Error
Modify Training Directions in Function Space to Reduce Generalization Error
Yi Yu
Wenlian Lu
Boyu Chen
29
0
0
25 Jul 2023
Constructing Extreme Learning Machines with zero Spectral Bias
Constructing Extreme Learning Machines with zero Spectral Bias
Kaumudi Joshi
V. Snigdha
A. K. Bhattacharya
31
2
0
19 Jul 2023
Quantitative CLTs in Deep Neural Networks
Quantitative CLTs in Deep Neural Networks
Stefano Favaro
Boris Hanin
Domenico Marinucci
I. Nourdin
G. Peccati
BDL
43
12
0
12 Jul 2023
Training-Free Neural Active Learning with Initialization-Robustness
  Guarantees
Training-Free Neural Active Learning with Initialization-Robustness Guarantees
Apivich Hemachandra
Zhongxiang Dai
Jasraj Singh
See-Kiong Ng
K. H. Low
AAML
36
6
0
07 Jun 2023
Fine-grained analysis of non-parametric estimation for pairwise learning
Fine-grained analysis of non-parametric estimation for pairwise learning
Junyu Zhou
Shuo Huang
Han Feng
Puyu Wang
Ding-Xuan Zhou
43
1
0
31 May 2023
Generalization Guarantees of Gradient Descent for Multi-Layer Neural
  Networks
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks
Puyu Wang
Yunwen Lei
Di Wang
Yiming Ying
Ding-Xuan Zhou
MLT
31
4
0
26 May 2023
Mind the spikes: Benign overfitting of kernels and neural networks in
  fixed dimension
Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension
Moritz Haas
David Holzmüller
U. V. Luxburg
Ingo Steinwart
MLT
40
14
0
23 May 2023
Tight conditions for when the NTK approximation is valid
Tight conditions for when the NTK approximation is valid
Enric Boix-Adserà
Etai Littwin
35
0
0
22 May 2023
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained
  Models
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
Guillermo Ortiz-Jiménez
Alessandro Favero
P. Frossard
MoMe
51
113
0
22 May 2023
Loss Spike in Training Neural Networks
Loss Spike in Training Neural Networks
Zhongwang Zhang
Z. Xu
38
5
0
20 May 2023
Understanding the Initial Condensation of Convolutional Neural Networks
Understanding the Initial Condensation of Convolutional Neural Networks
Zhangchen Zhou
Hanxu Zhou
Yuqing Li
Zhi-Qin John Xu
MLT
AI4CE
28
5
0
17 May 2023
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks
Eshaan Nichani
Alexandru Damian
Jason D. Lee
MLT
47
13
0
11 May 2023
Neural Exploitation and Exploration of Contextual Bandits
Neural Exploitation and Exploration of Contextual Bandits
Yikun Ban
Yuchen Yan
A. Banerjee
Jingrui He
44
8
0
05 May 2023
On the Eigenvalue Decay Rates of a Class of Neural-Network Related
  Kernel Functions Defined on General Domains
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains
Yicheng Li
Zixiong Yu
Y. Cotronis
Qian Lin
63
13
0
04 May 2023
Pretrained Embeddings for E-commerce Machine Learning: When it Fails and
  Why?
Pretrained Embeddings for E-commerce Machine Learning: When it Fails and Why?
Da Xu
Bo Yang
30
3
0
09 Apr 2023
Infinitely wide limits for deep Stable neural networks: sub-linear,
  linear and super-linear activation functions
Infinitely wide limits for deep Stable neural networks: sub-linear, linear and super-linear activation functions
Alberto Bordino
Stefano Favaro
S. Fortini
34
7
0
08 Apr 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean
  Field Neural Networks
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
Blake Bordelon
Cengiz Pehlevan
MLT
40
29
0
06 Apr 2023
Wide neural networks: From non-gaussian random fields at initialization
  to the NTK geometry of training
Wide neural networks: From non-gaussian random fields at initialization to the NTK geometry of training
Luís Carvalho
Joao L. Costa
José Mourao
Gonccalo Oliveira
AI4CE
26
1
0
06 Apr 2023
NTK-SAP: Improving neural network pruning by aligning training dynamics
NTK-SAP: Improving neural network pruning by aligning training dynamics
Yite Wang
Dawei Li
Ruoyu Sun
42
19
0
06 Apr 2023
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