157 citations · 713 across the 56 of their papers we have counts for
5 papers · 1 filter
Logistic Q-Learning
Joan Bas-Serrano, Sebastian Curi, Andreas Krause +1
We propose a new reinforcement learning algorithm derived from a regularized linear-programming formulation of optimal control in MDPs. The method is closely related to the classic…
A Unifying View of Optimism in Episodic Reinforcement Learning
Gergely Neu, Ciara Pike-Burke
The principle of optimism in the face of uncertainty underpins many theoretically successful reinforcement learning algorithms. In this paper we provide a general framework for des…
Online learning in MDPs with linear function approximation and bandit feedback
Gergely Neu, Julia Olkhovskaya
We consider an online learning problem where the learner interacts with a Markov decision process in a sequence of episodes, where the reward function is allowed to change between…
Efficient and Robust Algorithms for Adversarial Linear Contextual Bandits
Gergely Neu, Julia Olkhovskaya
We consider an adversarial variant of the classic -armed linear contextual bandit problem where the sequence of loss functions associated with each arm are allowed to change wit…
Fast Rates for Online Prediction with Abstention
Gergely Neu, Nikita Zhivotovskiy
In the setting of sequential prediction of individual -sequences with expert advice, we show that by allowing the learner to abstain from the prediction by paying a cost…