Richard Vidal
8 papers · 2020–2024 · 4 conferences · across top CS/AI conferences
Achievements
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๐ฃ Hot Topic Early Bird ๐บ๏ธ Taxonomy Completionist (12) ๐งญ Keyword Pioneer ๐ Interdisciplinary Bridge ๐ Conference Polyglot (4)
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Cross-Pollinator
(12)
๐ฅ
Unstoppable
(5)
Conferences
AISTATS (3)
ICML (2)
NIPS (2)
JMLR (1)
Top co-authors
Keywords
federated learning
(7)
model aggregation
(2)
distributed learning
(2)
stochastic gradient descent
(1)
non-convex optimization
(1)
binary classification
(1)
multi-task learning
(1)
gradient aggregation
(1)
expectation maximization
(1)
variance reduction
(1)
privacy preservation
(1)
machine unlearning
(1)
convergence analysis
(1)
empirical risk minimization
(1)
adversarial learning
(1)
asynchronous optimization
(1)
k-nearest neighbor
(1)
data stream
(1)
personalized model
(1)
representation learning
(1)
Papers
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
AISTATS 2024
A General Theory for Federated Optimization with Asynchronous and Heterogeneous Clients Updates
JMLR 2023
Federated Learning for Data Streams
AISTATS 2023
Personalized Federated Learning through Local Memorization
ICML 2022
Federated Multi-Task Learning under a Mixture of Distributions
NIPS 2021
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
ICML 2021
Free-rider Attacks on Model Aggregation in Federated Learning
AISTATS 2021
Throughput-Optimal Topology Design for Cross-Silo Federated Learning
NIPS 2020