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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.

P. Mangold, S. Samsonov, S. Labbi, I. Levin, R. Alami, A. Naumov, and E. Moulines. CoRR, (2024)

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Ruth Mangold

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A Decentralized Framework for Biostatistics and Privacy Concerns.P. Mangold, A. Filiot, M. Moussa, V. Sobanski, G. Ficheur, P. Andrey, and A. Lamer. EFMI-STC, volume 275 of Studies in Health Technology and Informatics, page 137-141. IOS Press, (2020)Differential Privacy has Bounded Impact on Fairness in Classification.P. Mangold, M. Perrot, A. Bellet, and M. Tommasi. ICML, volume 202 of Proceedings of Machine Learning Research, page 23681-23705. PMLR, (2023)Differentially Private Coordinate Descent for Composite Empirical Risk Minimization.P. Mangold, A. Bellet, J. Salmon, and M. Tommasi. CoRR, (2021)Differentially Private Coordinate Descent for Composite Empirical Risk Minimization.P. Mangold, A. Bellet, J. Salmon, and M. Tommasi. ICML, volume 162 of Proceedings of Machine Learning Research, page 14948-14978. PMLR, (2022)FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings.J. du Terrail, S. Ayed, E. Cyffers, F. Grimberg, C. He, R. Loeb, P. Mangold, T. Marchand, O. Marfoq, E. Mushtaq and 14 other author(s). NeurIPS, (2022)SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.P. Mangold, S. Samsonov, S. Labbi, I. Levin, R. Alami, A. Naumov, and E. Moulines. CoRR, (2024)Specifications for the Routine Implementation of Federated Learning in Hospitals Networks.A. Lamer, A. Filiot, Y. Bouillard, P. Mangold, P. Andrey, and J. Schiro. MIE, volume 281 of Studies in Health Technology and Informatics, page 128-132. IOS Press, (2021)High-Dimensional Private Empirical Risk Minimization by Greedy Coordinate Descent.P. Mangold, A. Bellet, J. Salmon, and M. Tommasi. CoRR, (2022)Fairness Certificates for Differentially Private Classification.P. Mangold, M. Perrot, A. Bellet, and M. Tommasi. CoRR, (2022)Exploiting Problem Structure in Privacy-Preserving Optimization and Machine Learning. (Exploitation de la Structure des Problèmes en Optimisation et en Apprentissage Automatique Respectueux de la Vie Privée).P. Mangold. University of Lille, France, (2023)

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Disambiguation of "Mangold, Paul"

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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.

Please choose a person to relate this publication to

Ruth Mangold

Günter Mangold

Walter Mangold

Wolfgang Mangold

Ulrike Mangold

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Mangold, Paul"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.

Please choose a person to relate this publication to

Ruth Mangold

Günter Mangold

Walter Mangold

Wolfgang Mangold

Ulrike Mangold

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Chicago
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SCAFFLSA: Quantifying and Eliminating Heterogeneity Bias in Federated Linear Stochastic Approximation and Temporal Difference Learning.