research
∙
01/30/2023
Regret Bounds for Markov Decision Processes with Recursive Optimized Certainty Equivalents
The optimized certainty equivalent (OCE) is a family of risk measures th...
share
research
∙
10/03/2022
Square-root regret bounds for continuous-time episodic Markov decision processes
We study reinforcement learning for continuous-time Markov decision proc...
research
∙
05/23/2022
Logarithmic regret bounds for continuous-time average-reward Markov decision processes
We consider reinforcement learning for continuous-time Markov decision p...
research
∙
07/31/2021
Debiasing Samples from Online Learning Using Bootstrap
It has been recently shown in the literature that the sample averages fr...
research
∙
07/08/2021
Sublinear Regret for Learning POMDPs
We study the model-based undiscounted reinforcement learning for partial...
research
∙
07/01/2020
Decentralized Stochastic Gradient Langevin Dynamics and Hamiltonian Monte Carlo
Stochastic gradient Langevin dynamics (SGLD) and stochastic gradient Ham...
research
∙
04/06/2020
Non-Convex Stochastic Optimization via Non-Reversible Stochastic Gradient Langevin Dynamics
Stochastic gradient Langevin dynamics (SGLD) is a poweful algorithm for ...
research
∙
01/26/2020
Regime Switching Bandits
We study a multi-armed bandit problem where the rewards exhibit regime-s...
research
∙
12/19/2018
Breaking Reversibility Accelerates Langevin Dynamics for Global Non-Convex Optimization
Langevin dynamics (LD) has been proven to be a powerful technique for op...
research
∙
09/12/2018