Igor Colin

According to our database1, Igor Colin authored at least 18 papers between 2015 and 2024.

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

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Differentially Private Model-Based Offline Reinforcement Learning.
CoRR, 2024

2023
Stable Bounds on the Duality Gap of Separable Nonconvex Optimization Problems.
Math. Oper. Res., May, 2023

Clustered Multi-Agent Linear Bandits.
CoRR, 2023

Price of Safety in Linear Best Arm Identification.
CoRR, 2023

Multi-Agent Best Arm Identification with Private Communications.
Proceedings of the International Conference on Machine Learning, 2023

2022
An α-No-Regret Algorithm For Graphical Bilinear Bandits.
CoRR, 2022

An $\alpha$-No-Regret Algorithm For Graphical Bilinear Bandits.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deciphering Lasso-based Classification Through a Large Dimensional Analysis of the Iterative Soft-Thresholding Algorithm.
Proceedings of the International Conference on Machine Learning, 2022

2021
Best Arm Identification in Graphical Bilinear Bandits.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Refined bounds for randomized experimental design.
CoRR, 2020

A Simple and Efficient Smoothing Method for Faster Optimization and Local Exploration.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
Theoretical Limits of Pipeline Parallel Optimization and Application to Distributed Deep Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Parallel Contextual Bandits in Wireless Handover Optimization.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

2016
Adapting machine learning methods to U-statistics. (Adaptation des méthodes d'apprentissage aux U-statistiques).
PhD thesis, 2016

Scaling-up Empirical Risk Minimization: Optimization of Incomplete $U$-statistics.
J. Mach. Learn. Res., 2016

Decentralized Topic Modelling with Latent Dirichlet Allocation.
CoRR, 2016

Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Extending Gossip Algorithms to Distributed Estimation of U-statistics.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015


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