We study the problem of minimizing the expected cost of binary searching for data where the access cost is not fixed and depends on the last accessed element, such as data stored i...
Gonzalo Navarro, Ricardo A. Baeza-Yates, Eduardo F...
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
In this paper, we study the following basic problem: After having executed a sequence of actions, find a sequence of actions that brings the agent back to the state just before th...
As microprocessors become increasingly complex, the techniques used to analyze and predict their behavior must become increasingly rigorous. This paper applies wavelet analysis te...