Franck Iutzeler

Orcid: 0000-0003-2537-380X

According to our database1, Franck Iutzeler authored at least 49 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
The Rate of Convergence of Bregman Proximal Methods: Local Geometry Versus Regularity Versus Sharpness.
SIAM J. Optim., 2024

<i>skwdro</i>: a library for Wasserstein distributionally robust machine learning.
CoRR, 2024

Derivatives of Stochastic Gradient Descent.
CoRR, 2024

What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Push-Pull With Device Sampling.
IEEE Trans. Autom. Control., December, 2023

Harnessing Structure in Composite Nonsmooth Minimization.
SIAM J. Optim., September, 2023

Newton acceleration on manifolds identified by proximal gradient methods.
Math. Program., 2023

Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism.
J. Mach. Learn. Res., 2022

On the rate of convergence of Bregman proximal methods in constrained variational inequalities.
CoRR, 2022

Entropy-regularized Wasserstein distributionally robust shape and topology optimization.
CoRR, 2022

Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation (Extended Abstract).
CoRR, 2022

2021
Distributed Learning with Sparse Communications by Identification.
SIAM J. Math. Data Sci., 2021

Proximal Gradient Methods with Adaptive Subspace Sampling.
Math. Oper. Res., 2021

Learning over No-Preferred and Preferred Sequence of Items for Robust Recommendation.
J. Artif. Intell. Res., 2021

The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities.
Proceedings of the Conference on Learning Theory, 2021

Optimization in Open Networks via Dual Averaging.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

Harnessing the Structure of some Optimization Problems. (Autour de l'utilisation de la structure dans certains problèmes d'optimisation).
, 2021

2020
A Distributed Flexible Delay-Tolerant Proximal Gradient Algorithm.
SIAM J. Optim., 2020

Asynchronous level bundle methods.
Math. Program., 2020

Rank-one partitioning: formalization, illustrative examples, and a new cluster enhancing strategy.
CoRR, 2020

On the interplay between acceleration and identification for the proximal gradient algorithm.
Comput. Optim. Appl., 2020

Randomized Progressive Hedging methods for multi-stage stochastic programming.
Ann. Oper. Res., 2020

Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sparse Asynchronous Distributed Learning.
Proceedings of the Neural Information Processing - 27th International Conference, 2020

2019
A generic online acceleration scheme for optimization algorithms via relaxation and inertia.
Optim. Methods Softw., 2019

On the convergence of single-call stochastic extra-gradient methods.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Distributed Projection on the Simplex and ℓ<sub>1</sub> Ball via ADMM and Gossip.
IEEE Signal Process. Lett., 2018

On the Proximal Gradient Algorithm with Alternated Inertia.
J. Optim. Theory Appl., 2018

Large-scale asynchronous distributed learning based on parameter exchanges.
Int. J. Data Sci. Anal., 2018

Asynchronous Distributed Learning with Sparse Communications and Identification.
CoRR, 2018

A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
Distributed Computation of Quantiles via ADMM.
IEEE Signal Process. Lett., 2017

Aggressive Sampling for Multi-class to Binary Reduction with Applications to Text Classification.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Distributed Production-Sharing Optimization and Application to Power Grid Networks.
IEEE Trans. Signal Inf. Process. over Networks, 2016

Explicit Convergence Rate of a Distributed Alternating Direction Method of Multipliers.
IEEE Trans. Autom. Control., 2016

A Coordinate Descent Primal-Dual Algorithm and Application to Distributed Asynchronous Optimization.
IEEE Trans. Autom. Control., 2016

Asynchronous Distributed Matrix Factorization with Similar User and Item Based Regularization.
Proceedings of the 10th ACM Conference on Recommender Systems, 2016

2014
A Stochastic Coordinate Descent Primal-Dual Algorithm and Applications to Large-Scale Composite Optimization.
CoRR, 2014

A stochastic coordinate descent primal-dual algorithm and applications.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014

A stochastic primal-dual algorithm for distributed asynchronous composite optimization.
Proceedings of the 2014 IEEE Global Conference on Signal and Information Processing, 2014

Linear convergence rate for distributed optimization with the alternating direction method of multipliers.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013
Distributed Estimation and Optimization for Asynchronous Networks. (Estimation et Optimisation Distribuée pour les Réseaux Asynchrones).
PhD thesis, 2013

Analysis of Sum-Weight-Like Algorithms for Averaging in Wireless Sensor Networks.
IEEE Trans. Signal Process., 2013

Fully distributed signal detection: Application to cognitive radio.
Proceedings of the 21st European Signal Processing Conference, 2013

Asynchronous distributed optimization using a randomized alternating direction method of multipliers.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

2012
Analysis of Max-Consensus Algorithms in Wireless Channels.
IEEE Trans. Signal Process., 2012

New broadcast based distributed averaging algorithm over wireless sensor networks.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Distributed estimation of the maximum value over a Wireless Sensor Network.
Proceedings of the Conference Record of the Forty Fifth Asilomar Conference on Signals, 2011


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