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On Lazy Training in Differentiable Programming

On Lazy Training in Differentiable Programming

19 December 2018
Lénaïc Chizat
Edouard Oyallon
Francis R. Bach
ArXivPDFHTML

Papers citing "On Lazy Training in Differentiable Programming"

50 / 222 papers shown
Title
L-SWAG: Layer-Sample Wise Activation with Gradients information for Zero-Shot NAS on Vision Transformers
L-SWAG: Layer-Sample Wise Activation with Gradients information for Zero-Shot NAS on Vision Transformers
S. Casarin
Sergio Escalera
Oswald Lanz
34
0
0
12 May 2025
Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures
Scaling Laws and Representation Learning in Simple Hierarchical Languages: Transformers vs. Convolutional Architectures
Francesco Cagnetta
Alessandro Favero
Antonio Sclocchi
M. Wyart
26
0
0
11 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
0
0
02 May 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
176
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
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
Devon Jarvis
Richard Klein
Benjamin Rosman
Andrew M. Saxe
MLT
66
1
0
08 Mar 2025
Feature Learning Beyond the Edge of Stability
Feature Learning Beyond the Edge of Stability
Dávid Terjék
MLT
46
0
0
18 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
Grokking at the Edge of Numerical Stability
Grokking at the Edge of Numerical Stability
Lucas Prieto
Melih Barsbey
Pedro A.M. Mediano
Tolga Birdal
48
3
0
08 Jan 2025
Optimization Insights into Deep Diagonal Linear Networks
Optimization Insights into Deep Diagonal Linear Networks
Hippolyte Labarrière
C. Molinari
Lorenzo Rosasco
S. Villa
Cristian Vega
76
0
0
21 Dec 2024
Infinite Width Limits of Self Supervised Neural Networks
Maximilian Fleissner
Gautham Govind Anil
D. Ghoshdastidar
SSL
160
0
0
17 Nov 2024
Robust Feature Learning for Multi-Index Models in High Dimensions
Robust Feature Learning for Multi-Index Models in High Dimensions
Alireza Mousavi-Hosseini
Adel Javanmard
Murat A. Erdogdu
OOD
AAML
44
1
0
21 Oct 2024
Offline-to-online Reinforcement Learning for Image-based Grasping with Scarce Demonstrations
Offline-to-online Reinforcement Learning for Image-based Grasping with Scarce Demonstrations
Bryan Chan
Anson Leung
James Bergstra
OffRL
OnRL
62
0
0
19 Oct 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
38
1
0
08 Oct 2024
SHAP values via sparse Fourier representation
SHAP values via sparse Fourier representation
Ali Gorji
Andisheh Amrollahi
A. Krause
FAtt
38
0
0
08 Oct 2024
Fast Training of Sinusoidal Neural Fields via Scaling Initialization
Fast Training of Sinusoidal Neural Fields via Scaling Initialization
Taesun Yeom
Sangyoon Lee
Jaeho Lee
61
2
0
07 Oct 2024
The Optimization Landscape of SGD Across the Feature Learning Strength
The Optimization Landscape of SGD Across the Feature Learning Strength
Alexander B. Atanasov
Alexandru Meterez
James B. Simon
Cengiz Pehlevan
43
2
0
06 Oct 2024
Attention layers provably solve single-location regression
Attention layers provably solve single-location regression
P. Marion
Raphael Berthier
Gérard Biau
Claire Boyer
152
2
0
02 Oct 2024
Investigating the Impact of Model Complexity in Large Language Models
Investigating the Impact of Model Complexity in Large Language Models
Jing Luo
Huiyuan Wang
Weiran Huang
39
0
0
01 Oct 2024
How Feature Learning Can Improve Neural Scaling Laws
How Feature Learning Can Improve Neural Scaling Laws
Blake Bordelon
Alexander B. Atanasov
Cengiz Pehlevan
57
12
0
26 Sep 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
38
3
0
22 Sep 2024
Continual learning with the neural tangent ensemble
Continual learning with the neural tangent ensemble
Ari S. Benjamin
Christian Pehle
Kyle Daruwalla
UQCV
70
0
0
30 Aug 2024
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning
Theoretical Insights into Overparameterized Models in Multi-Task and Replay-Based Continual Learning
Mohammadamin Banayeeanzade
Mahdi Soltanolkotabi
Mohammad Rostami
CLL
LRM
103
1
0
29 Aug 2024
Remove Symmetries to Control Model Expressivity and Improve Optimization
Remove Symmetries to Control Model Expressivity and Improve Optimization
Liu Ziyin
Yizhou Xu
Isaac Chuang
AAML
38
1
0
28 Aug 2024
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics
Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics
Alireza Mousavi-Hosseini
Denny Wu
Murat A. Erdogdu
MLT
AI4CE
35
6
0
14 Aug 2024
Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective
Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective
Jingren Liu
Zhong Ji
YunLong Yu
Jiale Cao
Yanwei Pang
Jungong Han
Xuelong Li
CLL
42
3
0
24 Jul 2024
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation
Lu Li
Tianze Zhang
Zhiqi Bu
Suyuchen Wang
Huan He
Jie Fu
Yonghui Wu
Jiang Bian
Yong Chen
Yoshua Bengio
FedML
MoMe
100
3
0
11 Jun 2024
Understanding and Minimising Outlier Features in Neural Network Training
Understanding and Minimising Outlier Features in Neural Network Training
Bobby He
Lorenzo Noci
Daniele Paliotta
Imanol Schlag
Thomas Hofmann
39
3
0
29 May 2024
When does compositional structure yield compositional generalization? A kernel theory
When does compositional structure yield compositional generalization? A kernel theory
Samuel Lippl
Kim Stachenfeld
NAI
CoGe
73
5
0
26 May 2024
Infinite Limits of Multi-head Transformer Dynamics
Infinite Limits of Multi-head Transformer Dynamics
Blake Bordelon
Hamza Tahir Chaudhry
Cengiz Pehlevan
AI4CE
47
9
0
24 May 2024
Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
Connectivity Shapes Implicit Regularization in Matrix Factorization Models for Matrix Completion
Zhiwei Bai
Jiajie Zhao
Yaoyu Zhang
AI4CE
37
0
0
22 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
NTK-Guided Few-Shot Class Incremental Learning
NTK-Guided Few-Shot Class Incremental Learning
Jingren Liu
Zhong Ji
Yanwei Pang
YunLong Yu
CLL
39
3
0
19 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
44
3
0
12 Mar 2024
Fine-tuning with Very Large Dropout
Fine-tuning with Very Large Dropout
Jianyu Zhang
Léon Bottou
44
1
0
01 Mar 2024
Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
Zhengqing Wu
Berfin Simsek
Francois Ged
ODL
45
0
0
08 Feb 2024
Critical Influence of Overparameterization on Sharpness-aware Minimization
Critical Influence of Overparameterization on Sharpness-aware Minimization
Sungbin Shin
Dongyeop Lee
Maksym Andriushchenko
Namhoon Lee
AAML
44
1
0
29 Nov 2023
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing:
  The Curses of Symmetry and Initialization
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
Nuoya Xiong
Lijun Ding
Simon S. Du
35
11
0
03 Oct 2023
Elephant Neural Networks: Born to Be a Continual Learner
Elephant Neural Networks: Born to Be a Continual Learner
Qingfeng Lan
A. R. Mahmood
CLL
48
9
0
02 Oct 2023
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
Fundamental Limits of Deep Learning-Based Binary Classifiers Trained with Hinge Loss
T. Getu
Georges Kaddoum
M. Bennis
40
1
0
13 Sep 2023
Gradient-Based Feature Learning under Structured Data
Gradient-Based Feature Learning under Structured Data
Alireza Mousavi-Hosseini
Denny Wu
Taiji Suzuki
Murat A. Erdogdu
MLT
37
18
0
07 Sep 2023
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and
  Luck
Pareto Frontiers in Neural Feature Learning: Data, Compute, Width, and Luck
Benjamin L. Edelman
Surbhi Goel
Sham Kakade
Eran Malach
Cyril Zhang
48
8
0
07 Sep 2023
Likelihood-ratio-based confidence intervals for neural networks
Likelihood-ratio-based confidence intervals for neural networks
Laurens Sluijterman
Eric Cator
Tom Heskes
UQCV
33
0
0
04 Aug 2023
Fading memory as inductive bias in residual recurrent networks
Fading memory as inductive bias in residual recurrent networks
I. Dubinin
Felix Effenberger
43
4
0
27 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
31
11
0
12 Jul 2023
The RL Perceptron: Generalisation Dynamics of Policy Learning in High
  Dimensions
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions
Nishil Patel
Sebastian Lee
Stefano Sarao Mannelli
Sebastian Goldt
Adrew Saxe
OffRL
28
3
0
17 Jun 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
29
3
0
26 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
110
0
22 May 2023
How Spurious Features Are Memorized: Precise Analysis for Random and NTK
  Features
How Spurious Features Are Memorized: Precise Analysis for Random and NTK Features
Simone Bombari
Marco Mondelli
AAML
28
4
0
20 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
44
13
0
11 May 2023
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