Kevin Scaman
23 papers · 2014–2025 · 7 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 6 separate collaboration groups - the largest holds only 39% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Kevin Scaman?
4 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Laurent Massoulié, Francis Bach, Sébastien Bubeck
9 papers
· 2017–2025
· ICML, AISTATS, NeurIPS
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In-depth Analysis of Low-rank Matrix Factorisation in a Federated Setting
AAAI 2025
When to Forget? Complexity Trade-offs in Machine Unlearning
ICML 2025
Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm
ICML 2024
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles
AISTATS 2024
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
AISTATS 2024
On Sample Optimality in Personalized Collaborative and Federated Learning
NeurIPS 2022
Optimal Convergence Rates for Convex Distributed Optimization in Networks
JMLR 2019
Optimal Algorithms for Non-Smooth Distributed Optimization in Networks
NeurIPS 2018
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks
ICML 2017