Mathieu Even
12 papers · 2021–2025 · 5 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 ↓+3 more ↓ Show less ↑
🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Gold 🗺️ Taxonomy Completionist (24) 🗃️ Keyword Collector (63)
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
🌈
Renaissance Researcher
(5)
Top co-authors
Research topics
Machine Learning
(11)
Optimization & Theory
(11)
Mathematics & Optimization
(5)
Core Methods
(4)
Optimization
(4)
Artificial Intelligence
(2)
Computer Science
(1)
Computer Vision
(1)
Deep Learning
(1)
Security & Privacy
(1)
Analysis
(1)
Application Areas
(1)
Applications
(1)
Core AI
(1)
Differential Privacy
(1)
Keywords
stochastic gradient descent
(4)
federated learning
(2)
variance reduction
(2)
distributed optimization
(2)
decentralized optimization
(2)
sample complexity
(2)
asynchronous stochastic gradient descent
(2)
convex optimization
(2)
non-convex optimization
(1)
distributed learning
(1)
differential privacy
(1)
point cloud
(1)
optimal transport
(1)
stochastic gradient
(1)
sparse regression
(1)
procrustes analysis
(1)
empirical risk minimization
(1)
system identification
(1)
generalization error
(1)
transfer learning
(1)
Papers
Long-Context Linear System Identification
ICLR 2025
Aligning Embeddings and Geometric Random Graphs: Informational Results and Computational Approaches for the Procrustes-Wasserstein Problem
NeurIPS 2024
Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization
AISTATS 2024
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles
AISTATS 2024
(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
NeurIPS 2023
Stochastic Gradient Descent under Markovian Sampling Schemes
ICML 2023
Asynchronous SGD Beats Minibatch SGD Under Arbitrary Delays
NeurIPS 2022
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and Averaging
NeurIPS 2022
On Sample Optimality in Personalized Collaborative and Federated Learning
NeurIPS 2022
Concentration of Non-Isotropic Random Tensors with Applications to Learning and Empirical Risk Minimization
COLT 2021
Continuized Accelerations of Deterministic and Stochastic Gradient Descents, and of Gossip Algorithms
NeurIPS 2021
Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction
ICML 2021