Franck Iutzeler
11 papers · 2017–2025 · 4 conferences · across top CS/AI conferences
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Conferences
NIPS (5)
ICML (4)
COLT (1)
JMLR (1)
Top co-authors
Keywords
stochastic optimization
(3)
convergence rate
(3)
asynchronous optimization
(2)
stochastic gradient descent
(2)
binary classification
(1)
variational inequality
(1)
stochastic gradient
(1)
linear convergence
(1)
distributed learning
(1)
empirical risk minimization
(1)
bregman divergence
(1)
multi-class classification
(1)
strong convexity
(1)
optimization theory
(1)
nonsmooth optimization
(1)
sampling strategy
(1)
parametric optimization
(1)
proximal gradient method
(1)
hyperparameter optimization
(1)
online learning
(1)
Papers
On the Private Estimation of Smooth Transport Maps
ICML 2025
The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations
ICML 2025
What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis
ICML 2024
Derivatives of Stochastic Gradient Descent in parametric optimization
NIPS 2024
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models
NIPS 2023
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism
JMLR 2022
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities
COLT 2021
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling
NIPS 2020
On the convergence of single-call stochastic extra-gradient methods
NIPS 2019
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning
ICML 2018
Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification
NIPS 2017