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02/22/2023
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes
The classical algorithms used in tabular reinforcement learning (Value I...
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01/30/2023
A Novel Framework for Policy Mirror Descent with General Parametrization and Linear Convergence
Modern policy optimization methods in applied reinforcement learning, su...
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09/30/2022
Linear Convergence for Natural Policy Gradient with Log-linear Policy Parametrization
We analyze the convergence rate of the unregularized natural policy grad...
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02/23/2022
Exponential Tail Local Rademacher Complexity Risk Bounds Without the Bernstein Condition
The local Rademacher complexity framework is one of the most successful ...
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11/25/2021
Time-independent Generalization Bounds for SGLD in Non-convex Settings
We establish generalization error bounds for stochastic gradient Langevi...
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10/21/2021
On Optimal Interpolation In Linear Regression
Understanding when and why interpolating methods generalize well has rec...
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09/23/2021
Dimension-Free Rates for Natural Policy Gradient in Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning is a decentralized paradi...
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08/26/2021
Comparing Classes of Estimators: When does Gradient Descent Beat Ridge Regression in Linear Models?
Modern methods for learning from data depend on many tuning parameters, ...
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05/28/2021
Implicit Regularization in Matrix Sensing via Mirror Descent
We study discrete-time mirror descent applied to the unregularized empir...
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05/08/2021
Nearly Minimax-Optimal Rates for Noisy Sparse Phase Retrieval via Early-Stopped Mirror Descent
This paper studies early-stopped mirror descent applied to noisy sparse ...
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10/20/2020
A Continuous-Time Mirror Descent Approach to Sparse Phase Retrieval
We analyze continuous-time mirror descent applied to sparse phase retrie...
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07/01/2020
Decentralised Learning with Random Features and Distributed Gradient Descent
We investigate the generalisation performance of Distributed Gradient De...
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06/01/2020
Hadamard Wirtinger Flow for Sparse Phase Retrieval
We consider the problem of reconstructing an n-dimensional k-sparse sign...
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02/01/2020
The Statistical Complexity of Early Stopped Mirror Descent
Recently there has been a surge of interest in understanding implicit re...
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12/03/2019
Decentralised Sparse Multi-Task Regression
We consider a sparse multi-task regression framework for fitting a colle...
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09/11/2019
Implicit Regularization for Optimal Sparse Recovery
We investigate implicit regularization schemes for gradient descent meth...
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05/08/2019
Optimal Statistical Rates for Decentralised Non-Parametric Regression with Linear Speed-Up
We analyse the learning performance of Distributed Gradient Descent in t...
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10/10/2018
Decentralized Cooperative Stochastic Multi-armed Bandits
We study a decentralized cooperative stochastic multi-armed bandit probl...
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09/18/2018
Graph-Dependent Implicit Regularisation for Distributed Stochastic Subgradient Descent
We propose graph-dependent implicit regularisation strategies for distri...
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02/12/2016
Scale-free network optimization: foundations and algorithms
We investigate the fundamental principles that drive the development of ...
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06/06/2015