It has been noted that many realistic graphs have a power law degree distribution and exhibit the small world phenomenon. We present drawing methods influenced by recent developm...
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
This paper introduces a geometrically inspired large-margin classifier that can be a better alternative to the Support Vector Machines (SVMs) for the classification problems with ...
This paper presents a practical technique to automatically compute approximations of polygonal representations of 3D objects. It is based on a previously developed model simplific...
In this paper we present a new approach to derive heavy-traffic asymptotics for polling models. We consider the classical cyclic polling model with exhaustive or gated service at ...