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In Search of the Real Inductive Bias: On the Role of Implicit
  Regularization in Deep Learning

In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning

20 December 2014
Behnam Neyshabur
Ryota Tomioka
Nathan Srebro
    AI4CE
ArXivPDFHTML

Papers citing "In Search of the Real Inductive Bias: On the Role of Implicit Regularization in Deep Learning"

16 / 16 papers shown
Title
Gradient Descent Robustly Learns the Intrinsic Dimension of Data in Training Convolutional Neural Networks
Gradient Descent Robustly Learns the Intrinsic Dimension of Data in Training Convolutional Neural Networks
Chenyang Zhang
Peifeng Gao
Difan Zou
Yuan Cao
OOD
MLT
106
0
0
11 Apr 2025
High-entropy Advantage in Neural Networks' Generalizability
High-entropy Advantage in Neural Networks' Generalizability
Entao Yang
Wei Wei
Yue Shang
Ge Zhang
AI4CE
80
0
0
17 Mar 2025
The late-stage training dynamics of (stochastic) subgradient descent on homogeneous neural networks
Sholom Schechtman
Nicolas Schreuder
383
0
0
08 Feb 2025
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Deep Weight Factorization: Sparse Learning Through the Lens of Artificial Symmetries
Chris Kolb
T. Weber
Bernd Bischl
David Rügamer
212
1
0
04 Feb 2025
The Effects of Multi-Task Learning on ReLU Neural Network Functions
The Effects of Multi-Task Learning on ReLU Neural Network Functions
Julia B. Nakhleh
Joseph Shenouda
Robert D. Nowak
53
1
0
29 Oct 2024
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens
Bilinear Sequence Regression: A Model for Learning from Long Sequences of High-dimensional Tokens
Vittorio Erba
Emanuele Troiani
Luca Biggio
Antoine Maillard
Lenka Zdeborová
122
1
0
24 Oct 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
62
1
0
28 Aug 2024
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
Bias of Stochastic Gradient Descent or the Architecture: Disentangling the Effects of Overparameterization of Neural Networks
Amit Peleg
Matthias Hein
43
0
0
04 Jul 2024
Information-Theoretic Generalization Bounds for Deep Neural Networks
Information-Theoretic Generalization Bounds for Deep Neural Networks
Haiyun He
Christina Lee Yu
75
5
0
04 Apr 2024
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models
Jeremy E. Cohen
Valentin Leplat
72
1
0
27 Mar 2024
Neural Redshift: Random Networks are not Random Functions
Neural Redshift: Random Networks are not Random Functions
Damien Teney
A. Nicolicioiu
Valentin Hartmann
Ehsan Abbasnejad
117
22
0
04 Mar 2024
Asynchronous Graph Generator
Asynchronous Graph Generator
Christopher P. Ley
Felipe Tobar
AI4TS
75
0
0
29 Sep 2023
Penalising the biases in norm regularisation enforces sparsity
Penalising the biases in norm regularisation enforces sparsity
Etienne Boursier
Nicolas Flammarion
71
17
0
02 Mar 2023
COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks
COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks
Md. Ismail Hossain
Mohammed Rakib
M. M. L. Elahi
Nabeel Mohammed
Shafin Rahman
71
1
0
24 Dec 2022
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization
  as a Case Study
Can Implicit Bias Explain Generalization? Stochastic Convex Optimization as a Case Study
Assaf Dauber
M. Feder
Tomer Koren
Roi Livni
36
24
0
13 Mar 2020
From average case complexity to improper learning complexity
From average case complexity to improper learning complexity
Amit Daniely
N. Linial
Shai Shalev-Shwartz
64
120
0
10 Nov 2013
1