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Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian
  Compression Approach

Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach

16 April 2018
Wenda Zhou
Victor Veitch
Morgane Austern
Ryan P. Adams
Peter Orbanz
ArXivPDFHTML

Papers citing "Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach"

40 / 40 papers shown
Title
Information-Theoretic Generalization Bounds for Deep Neural Networks
Information-Theoretic Generalization Bounds for Deep Neural Networks
Haiyun He
Christina Lee Yu
35
4
0
04 Apr 2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications
Huayi Tang
Yong Liu
57
1
0
08 Nov 2023
Understanding Deep Neural Networks via Linear Separability of Hidden
  Layers
Understanding Deep Neural Networks via Linear Separability of Hidden Layers
Chao Zhang
Xinyuan Chen
Wensheng Li
Lixue Liu
Wei Wu
Dacheng Tao
18
3
0
26 Jul 2023
More PAC-Bayes bounds: From bounded losses, to losses with general tail
  behaviors, to anytime validity
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity
Borja Rodríguez Gálvez
Ragnar Thobaben
Mikael Skoglund
26
9
0
21 Jun 2023
PAC-Bayes Compression Bounds So Tight That They Can Explain
  Generalization
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization
Sanae Lotfi
Marc Finzi
Sanyam Kapoor
Andres Potapczynski
Micah Goldblum
A. Wilson
BDL
MLT
AI4CE
21
51
0
24 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport
Instance-Dependent Generalization Bounds via Optimal Transport
Songyan Hou
Parnian Kassraie
Anastasis Kratsios
Andreas Krause
Jonas Rothfuss
20
6
0
02 Nov 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent
  Kernel
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel
Sungyub Kim
Si-hun Park
Kyungsu Kim
Eunho Yang
BDL
24
4
0
30 Sep 2022
Generalisation under gradient descent via deterministic PAC-Bayes
Generalisation under gradient descent via deterministic PAC-Bayes
Eugenio Clerico
Tyler Farghly
George Deligiannidis
Benjamin Guedj
Arnaud Doucet
26
4
0
06 Sep 2022
On Rademacher Complexity-based Generalization Bounds for Deep Learning
On Rademacher Complexity-based Generalization Bounds for Deep Learning
Lan V. Truong
MLT
37
13
0
08 Aug 2022
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners
Anthony Sicilia
Katherine Atwell
Malihe Alikhani
Seong Jae Hwang
BDL
51
9
0
12 Jul 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity
Benefits of Additive Noise in Composing Classes with Bounded Capacity
A. F. Pour
H. Ashtiani
15
3
0
14 Jun 2022
Trajectory-dependent Generalization Bounds for Deep Neural Networks via
  Fractional Brownian Motion
Trajectory-dependent Generalization Bounds for Deep Neural Networks via Fractional Brownian Motion
Chengli Tan
Jiang Zhang
Junmin Liu
35
1
0
09 Jun 2022
Adversarial robustness of sparse local Lipschitz predictors
Adversarial robustness of sparse local Lipschitz predictors
Ramchandran Muthukumar
Jeremias Sulam
AAML
32
13
0
26 Feb 2022
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Bayesian Model Selection, the Marginal Likelihood, and Generalization
Sanae Lotfi
Pavel Izmailov
Gregory W. Benton
Micah Goldblum
A. Wilson
UQCV
BDL
52
56
0
23 Feb 2022
On change of measure inequalities for $f$-divergences
On change of measure inequalities for fff-divergences
Antoine Picard-Weibel
Benjamin Guedj
25
13
0
11 Feb 2022
Demystify Optimization and Generalization of Over-parameterized
  PAC-Bayesian Learning
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
Non-Vacuous Generalisation Bounds for Shallow Neural Networks
Non-Vacuous Generalisation Bounds for Shallow Neural Networks
Felix Biggs
Benjamin Guedj
BDL
30
26
0
03 Feb 2022
Fortuitous Forgetting in Connectionist Networks
Fortuitous Forgetting in Connectionist Networks
Hattie Zhou
Ankit Vani
Hugo Larochelle
Aaron Courville
CLL
6
42
0
01 Feb 2022
Generalization Error Bounds on Deep Learning with Markov Datasets
Generalization Error Bounds on Deep Learning with Markov Datasets
Lan V. Truong
18
8
0
23 Dec 2021
On the Convergence of Shallow Neural Network Training with Randomly
  Masked Neurons
On the Convergence of Shallow Neural Network Training with Randomly Masked Neurons
Fangshuo Liao
Anastasios Kyrillidis
36
16
0
05 Dec 2021
Improved Regularization and Robustness for Fine-tuning in Neural
  Networks
Improved Regularization and Robustness for Fine-tuning in Neural Networks
Dongyue Li
Hongyang R. Zhang
NoLa
49
54
0
08 Nov 2021
PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks
  with Probabilities over Representations
PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations
Louis Fortier-Dubois
Gaël Letarte
Benjamin Leblanc
Franccois Laviolette
Pascal Germain
UQCV
14
0
0
28 Oct 2021
Does the Data Induce Capacity Control in Deep Learning?
Does the Data Induce Capacity Control in Deep Learning?
Rubing Yang
J. Mao
Pratik Chaudhari
22
15
0
27 Oct 2021
User-friendly introduction to PAC-Bayes bounds
User-friendly introduction to PAC-Bayes bounds
Pierre Alquier
FedML
39
196
0
21 Oct 2021
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity
  on Pruned Neural Networks
Why Lottery Ticket Wins? A Theoretical Perspective of Sample Complexity on Pruned Neural Networks
Shuai Zhang
Meng Wang
Sijia Liu
Pin-Yu Chen
Jinjun Xiong
UQCV
MLT
21
13
0
12 Oct 2021
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate
  bounds that handle general VC classes
PAC-Bayes, MAC-Bayes and Conditional Mutual Information: Fast rate bounds that handle general VC classes
Peter Grünwald
Thomas Steinke
Lydia Zakynthinou
21
29
0
17 Jun 2021
RATT: Leveraging Unlabeled Data to Guarantee Generalization
RATT: Leveraging Unlabeled Data to Guarantee Generalization
Saurabh Garg
Sivaraman Balakrishnan
J. Zico Kolter
Zachary Chase Lipton
25
29
0
01 May 2021
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform
  Stability
Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability
Alec Farid
Anirudha Majumdar
21
34
0
12 Feb 2021
For self-supervised learning, Rationality implies generalization,
  provably
For self-supervised learning, Rationality implies generalization, provably
Yamini Bansal
Gal Kaplun
Boaz Barak
OOD
SSL
58
22
0
16 Oct 2020
Generalization Bounds via Information Density and Conditional
  Information Density
Generalization Bounds via Information Density and Conditional Information Density
Fredrik Hellström
G. Durisi
13
65
0
16 May 2020
Minimum Description Length Revisited
Minimum Description Length Revisited
Peter Grünwald
Teemu Roos
15
64
0
21 Aug 2019
What does it mean to understand a neural network?
What does it mean to understand a neural network?
Timothy Lillicrap
Konrad Paul Kording
8
42
0
15 Jul 2019
Chaining Meets Chain Rule: Multilevel Entropic Regularization and
  Training of Neural Nets
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets
Amir-Reza Asadi
Emmanuel Abbe
BDL
AI4CE
23
13
0
26 Jun 2019
PAC-Bayes Un-Expected Bernstein Inequality
PAC-Bayes Un-Expected Bernstein Inequality
Zakaria Mhammedi
Peter Grünwald
Benjamin Guedj
14
46
0
31 May 2019
Norm-based generalisation bounds for multi-class convolutional neural
  networks
Norm-based generalisation bounds for multi-class convolutional neural networks
Antoine Ledent
Waleed Mustafa
Yunwen Lei
Marius Kloft
8
5
0
29 May 2019
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural
  Networks
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks
Gaël Letarte
Pascal Germain
Benjamin Guedj
Franccois Laviolette
MQ
AI4CE
UQCV
20
54
0
24 May 2019
Fine-Grained Analysis of Optimization and Generalization for
  Overparameterized Two-Layer Neural Networks
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks
Sanjeev Arora
S. Du
Wei Hu
Zhiyuan Li
Ruosong Wang
MLT
35
961
0
24 Jan 2019
PAC-Bayesian Margin Bounds for Convolutional Neural Networks
PAC-Bayesian Margin Bounds for Convolutional Neural Networks
Konstantinos Pitas
Mike Davies
P. Vandergheynst
BDL
41
12
0
30 Dec 2017
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
278
2,888
0
15 Sep 2016
Pac-Bayesian Supervised Classification: The Thermodynamics of
  Statistical Learning
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning
O. Catoni
142
453
0
03 Dec 2007
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