Patrick Rebeschini

Orcid: 0000-0001-7772-4160

According to our database1, Patrick Rebeschini authored at least 32 papers between 2014 and 2024.

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

Timeline

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PhD thesis 
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Bibliography

2024
Robust Gradient Descent for Phase Retrieval.
CoRR, 2024

Differentiable Cost-Parameterized Monge Map Estimators.
CoRR, 2024

Meta-learning the mirror map in policy mirror descent.
CoRR, 2024

Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Generalization Bounds for Label Noise Stochastic Gradient Descent.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023
A Novel Framework for Policy Mirror Descent with General Parametrization and Linear Convergence.
CoRR, 2023

Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022
Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization.
CoRR, 2022

Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition.
CoRR, 2022

2021
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning.
CoRR, 2021

Comparing Classes of Estimators: When does Gradient Descent Beat Ridge Regression in Linear Models?
CoRR, 2021

Nearly Minimax-Optimal Rates for Noisy Sparse Phase Retrieval via Early-Stopped Mirror Descent.
CoRR, 2021

Implicit Regularization in Matrix Sensing via Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Distributed Machine Learning with Sparse Heterogeneous Data.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Optimal Interpolation in Linear Regression.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Time-independent Generalization Bounds for SGLD in Non-convex Settings.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Hadamard Wirtinger Flow for Sparse Phase Retrieval.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent.
J. Mach. Learn. Res., 2020

A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The Statistical Complexity of Early-Stopped Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Decentralised Learning with Random Features and Distributed Gradient Descent.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Locality in Network Optimization.
IEEE Trans. Control. Netw. Syst., 2019

A New Approach to Laplacian Solvers and Flow Problems.
J. Mach. Learn. Res., 2019

Implicit Regularization for Optimal Sparse Recovery.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Decentralized Cooperative Stochastic Bandits.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Decentralized Cooperative Stochastic Multi-armed Bandits.
CoRR, 2018

2017
Accelerated consensus via Min-Sum Splitting.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Decay of correlation in network flow problems.
Proceedings of the 2016 Annual Conference on Information Science and Systems, 2016

2015
Fast Mixing for Discrete Point Processes.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Nonlinear Filtering in High Dimension
PhD thesis, 2014


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