Abstract. The aim of this work is to forecast future events in financial data sets, in particular, we focus our attention on situations where positive instances are rare, which fal...
There is growing public concern about personal data collected by both private and public sectors. People have very little control over what kinds of data are stored and how such da...
We present Policy Gradient Actor-Critic (PGAC), a new model-free Reinforcement Learning (RL) method for creating limited-memory stochastic policies for Partially Observable Markov ...
Background: The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function c...
Markov decision processes (MDPs) with discrete and continuous state and action components can be solved efficiently by hybrid approximate linear programming (HALP). The main idea ...