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Limitations of Information-Theoretic Generalization Bounds for Gradient
  Descent Methods in Stochastic Convex Optimization

Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization

27 December 2022
Mahdi Haghifam
Borja Rodríguez Gálvez
Ragnar Thobaben
Mikael Skoglund
Daniel M. Roy
Gintare Karolina Dziugaite
ArXivPDFHTML

Papers citing "Limitations of Information-Theoretic Generalization Bounds for Gradient Descent Methods in Stochastic Convex Optimization"

10 / 10 papers shown
Title
Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior
Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior
Milad Sefidgaran
Abdellatif Zaidi
Piotr Krasnowski
44
0
0
25 Apr 2025
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
Milad Sefidgaran
A. Zaidi
Piotr Krasnowski
77
1
0
21 Feb 2025
Generalization Guarantees via Algorithm-dependent Rademacher Complexity
Generalization Guarantees via Algorithm-dependent Rademacher Complexity
Sarah Sachs
T. Erven
Liam Hodgkinson
Rajiv Khanna
Umut Simsekli
14
3
0
04 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
13
9
0
21 Jun 2023
Tighter Information-Theoretic Generalization Bounds from Supersamples
Tighter Information-Theoretic Generalization Bounds from Supersamples
Ziqiao Wang
Yongyi Mao
19
17
0
05 Feb 2023
Formal limitations of sample-wise information-theoretic generalization
  bounds
Formal limitations of sample-wise information-theoretic generalization bounds
Hrayr Harutyunyan
Greg Ver Steeg
Aram Galstyan
11
2
0
13 May 2022
On the Generalization of Models Trained with SGD: Information-Theoretic
  Bounds and Implications
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
Ziqiao Wang
Yongyi Mao
FedML
MLT
32
22
0
07 Oct 2021
Information-theoretic generalization bounds for black-box learning
  algorithms
Information-theoretic generalization bounds for black-box learning algorithms
Hrayr Harutyunyan
Maxim Raginsky
Greg Ver Steeg
Aram Galstyan
32
41
0
04 Oct 2021
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs
SGD: The Role of Implicit Regularization, Batch-size and Multiple-epochs
Satyen Kale
Ayush Sekhari
Karthik Sridharan
173
28
0
11 Jul 2021
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent
  Estimates
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates
Jeffrey Negrea
Mahdi Haghifam
Gintare Karolina Dziugaite
Ashish Khisti
Daniel M. Roy
FedML
105
146
0
06 Nov 2019
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