Patrick Rebeschini
23 papers · 2015–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (6) π Academic Marathon (10) π§ Keyword Pioneer π Interdisciplinary Bridge π Cross-Pollinator (12)
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Taxonomy Completionist
(32)
π§
Keyword Pioneer
π
Conference Polyglot
(6)
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(93)
π
Century Club
(23)
β‘
Prolific Year
(5)
Conferences
NIPS (12)
AISTATS (4)
JMLR (3)
ICLR (2)
COLT (1)
ICML (1)
Top co-authors
Keywords
implicit regularization
(5)
gradient descent
(5)
distributed learning
(4)
mirror descent
(4)
non-convex optimization
(3)
empirical risk minimization
(3)
algorithmic stability
(3)
stochastic gradient descent
(2)
generalization bound
(2)
sparse phase retrieval
(2)
signal reconstruction
(2)
distributed optimization
(2)
sample complexity
(1)
convergence analysis
(1)
model selection
(1)
ridge regression
(1)
policy gradient
(1)
sparse recovery
(1)
statistical learning theory
(1)
markov decision process
(1)
Papers
Learning mirror maps in policy mirror descent
ICLR 2025
Black-Box Uniform Stability for Non-Euclidean Empirical Risk Minimization
AISTATS 2025
Robust Gradient Descent for Phase Retrieval
AISTATS 2025
Generalization Bounds for Label Noise Stochastic Gradient Descent
AISTATS 2024
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition
JMLR 2024
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
ICLR 2024
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes
NIPS 2023
A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence
NIPS 2023
Implicit Regularization in Matrix Sensing via Mirror Descent
NIPS 2021
On Optimal Interpolation in Linear Regression
NIPS 2021
Hadamard Wirtinger Flow for Sparse Phase Retrieval
AISTATS 2021
Distributed Machine Learning with Sparse Heterogeneous Data
NIPS 2021
Time-independent Generalization Bounds for SGLD in Non-convex Settings
NIPS 2021
A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval
NIPS 2020
The Statistical Complexity of Early-Stopped Mirror Descent
NIPS 2020
Decentralised Learning with Random Features and Distributed Gradient Descent
ICML 2020
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent
JMLR 2020
A New Approach to Laplacian Solvers and Flow Problems
JMLR 2019
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
NIPS 2019
Decentralized Cooperative Stochastic Bandits
NIPS 2019
Implicit Regularization for Optimal Sparse Recovery
NIPS 2019
Accelerated consensus via Min-Sum Splitting
NIPS 2017
Fast Mixing for Discrete Point Processes
COLT 2015