Actor-Critic based approaches were among the first to address reinforcement learning in a general setting. Recently, these algorithms have gained renewed interest due to their gen...
The rapid advance of computer technologies in data processing, collection, and storage has provided unparalleled opportunities to expand capabilities in production, services, comm...
In this paper we propose a new algorithm for learning polyhedral classifiers. In contrast to existing methods for learning polyhedral classifier which solve a constrained optimiza...
Abstract. We prove pointwise a posteriori error estimates for semi- and fullydiscrete finite element methods for approximating the solution u to a parabolic model problem. Our esti...
The Monte-Carlo (MC) technique is a traditional solution for a reliable statistical analysis, and in contrast to probabilistic methods, it can account for any complicate model. How...