Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schem...
Real life datasets often suffer from the problem of class imbalance, which thwarts supervised learning process. In such data sets examples of positive (minority) class are signific...
The paper presents an approach to the task of automatic document categorization in the field of economics. Since the documents can be annotated with multiple keywords (labels), we ...
The problem of characterizing learnability is the most basic question of statistical learning theory. A fundamental and long-standing answer, at least for the case of supervised c...
: Significant progress has been made by the computer vision community in recent years along two fronts: (i) developing complex spatial-temporal models for object registration and t...