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2005.02503
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Information-Theoretic Bounds on the Generalization Error and Privacy Leakage in Federated Learning
International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2020
5 May 2020
Semih Yagli
Alex Dytso
H. Vincent Poor
FedML
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Papers citing
"Information-Theoretic Bounds on the Generalization Error and Privacy Leakage in Federated Learning"
19 / 19 papers shown
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang
Cheng Long
Yongyi Mao
FedML
412
2
0
06 Mar 2025
Heterogeneity Matters even More in Distributed Learning: Study from Generalization Perspective
Masoud Kavian
Romain Chor
Milad Sefidgaran
Abdellatif Zaidi
FedML
482
2
0
03 Mar 2025
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization
Wenrui Yu
Qiongxiu Li
Milan Lopuhaä-Zwakenberg
Mads Græsbøll Christensen
Richard Heusdens
FedML
229
11
0
12 Jul 2024
Improved Generalization Bounds for Communication Efficient Federated Learning
Peyman Gholami
H. Seferoglu
FedML
AI4CE
428
6
0
17 Apr 2024
Scalable Federated Learning for Clients with Different Input Image Sizes and Numbers of Output Categories
International Conference on Machine Learning and Applications (ICMLA), 2023
Shuhei Nitta
Taiji Suzuki
Albert Rodríguez Mulet
A. Yaguchi
Ryusuke Hirai
FedML
231
0
0
15 Nov 2023
Information-Theoretic Generalization Analysis for Topology-aware Heterogeneous Federated Edge Learning over Noisy Channels
IEEE Signal Processing Letters (IEEE SPL), 2023
Zheshun Wu
Zenglin Xu
Hongfang Yu
Jie Liu
347
7
0
25 Oct 2023
Federated Learning with Nonvacuous Generalisation Bounds
Pierre Jobic
Maxime Haddouche
Benjamin Guedj
FedML
296
4
0
17 Oct 2023
Advocating for the Silent: Enhancing Federated Generalization for Non-Participating Clients
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023
Zheshun Wu
Zenglin Xu
Dun Zeng
Qifan Wang
Jie Liu
FedML
535
4
0
11 Oct 2023
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!
International Conference on Machine Learning (ICML), 2023
Romain Chor
Abdellatif Zaidi
Milad Sefidgaran
Yijun Wan
FedML
324
11
0
09 Jun 2023
Understanding How Consistency Works in Federated Learning via Stage-wise Relaxed Initialization
Neural Information Processing Systems (NeurIPS), 2023
Yan Sun
Li Shen
Dacheng Tao
FedML
253
22
0
09 Jun 2023
Federated Learning under Covariate Shifts with Generalization Guarantees
Ali Ramezani-Kebrya
Fanghui Liu
Thomas Pethick
Grigorios G. Chrysos
Volkan Cevher
FedML
OOD
390
12
0
08 Jun 2023
More Communication Does Not Result in Smaller Generalization Error in Federated Learning
International Symposium on Information Theory (ISIT), 2023
Abdellatif Zaidi
Romain Chor
Milad Sefidgaran
FedML
AI4CE
284
11
0
24 Apr 2023
Quantifying the Impact of Label Noise on Federated Learning
Shuqi Ke
Chao Huang
Xin Liu
FedML
456
8
0
15 Nov 2022
Rate-Distortion Theoretic Bounds on Generalization Error for Distributed Learning
Neural Information Processing Systems (NeurIPS), 2022
Romain Chor
Abdellatif Zaidi
Milad Sefidgaran
FedML
336
18
0
06 Jun 2022
Improved Information Theoretic Generalization Bounds for Distributed and Federated Learning
International Symposium on Information Theory (ISIT), 2022
L. P. Barnes
Alex Dytso
H. V. Poor
FedML
282
29
0
04 Feb 2022
What Do We Mean by Generalization in Federated Learning?
Honglin Yuan
Warren Morningstar
Lin Ning
K. Singhal
OOD
FedML
385
97
0
27 Oct 2021
An Information-Theoretic Analysis of The Cost of Decentralization for Learning and Inference Under Privacy Constraints
Sharu Theresa Jose
Osvaldo Simeone
FedML
176
0
0
11 Oct 2021
Communication efficient privacy-preserving distributed optimization using adaptive differential quantization
Signal Processing (Signal Process.), 2021
Qiongxiu Li
Richard Heusdens
M. G. Christensen
202
17
0
30 May 2021
Generalization Bounds for Noisy Iterative Algorithms Using Properties of Additive Noise Channels
Journal of machine learning research (JMLR), 2021
Hao Wang
Rui Gao
Flavio du Pin Calmon
370
20
0
05 Feb 2021
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