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Richard Vidal

Evaluating the Energy Consumption of Machine Learning: Systematic Literature Review and Experiments

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Aug 27, 2024
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Fed-BioMed: Open, Transparent and Trusted Federated Learning for Real-world Healthcare Applications

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Apr 24, 2023
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Federated Learning for Data Streams

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Jan 04, 2023
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Sequential Informed Federated Unlearning: Efficient and Provable Client Unlearning in Federated Optimization

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Nov 21, 2022
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A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates

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Jun 21, 2022
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Personalized Federated Learning through Local Memorization

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Nov 17, 2021
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Federated Multi-Task Learning under a Mixture of Distributions

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Aug 23, 2021
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On The Impact of Client Sampling on Federated Learning Convergence

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Jul 26, 2021
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Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning

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May 21, 2021
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Throughput-Optimal Topology Design for Cross-Silo Federated Learning

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Oct 23, 2020
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