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2212.13556
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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
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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
Milad Sefidgaran
Abdellatif Zaidi
Piotr Krasnowski
44
0
0
25 Apr 2025
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
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
Borja Rodríguez Gálvez
Ragnar Thobaben
Mikael Skoglund
13
9
0
21 Jun 2023
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
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
Ziqiao Wang
Yongyi Mao
FedML
MLT
32
22
0
07 Oct 2021
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
Satyen Kale
Ayush Sekhari
Karthik Sridharan
173
28
0
11 Jul 2021
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
1