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Kevin Scaman

Kevin Scaman

Researcher

INRIA

To be completed

Intérêts
Éducation

Récents

  • In-Depth Analysis of Low-rank Matrix Factorisation in a Federated Setting
  • Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
  • Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles
  • SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization

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