Richard Vidal
8 papers · 2020–2024 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓
🌍
Conference Polyglot · Bronze
🌉
Interdisciplinary Bridge · Bronze
🗺️
Taxonomy Completionist
(22)
🐣
Hot Topic Early Bird
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Machine Learning
(8)
Artificial Intelligence
(7)
Learning Paradigms · Artificial Intelligence
(7)
Learning Paradigms · Machine Learning
(6)
Learning Types
(5)
Mathematics & Optimization
(3)
Optimization
(3)
Optimization & Theory
(3)
Application Areas
(2)
Core Methods
(2)
Bayesian & Probabilistic
(1)
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
Clustered Sampling: Low-Variance and Improved Representativity for Clients Selection in Federated Learning
ICML 2021
Federated Multi-Task Learning under a Mixture of Distributions
NeurIPS 2021
Free-rider Attacks on Model Aggregation in Federated Learning
AISTATS 2021
Throughput-Optimal Topology Design for Cross-Silo Federated Learning
NeurIPS 2020