Factored representations, model-based learning, and hierarchies are well-studied techniques for improving the learning efficiency of reinforcement-learning algorithms in large-sca...
Carlos Diuk, Alexander L. Strehl, Michael L. Littm...
Customizing architectures for particular applications is a promising approach to yield highly energy-efficient designs for embedded systems. This work explores the benefits of arc...
This paper describes several novel timing attacks against the common table-driven software implementation of the AES cipher. We define a general attack strategy using a simplified ...
Utilizing graphics hardware for general purpose numerical computations has become a topic of considerable interest. The implementation of streaming algorithms, typified by highly ...
Nowadays, cross-lingual Information Retrieval (IR) is one of the greatest challenges to deal with. Besides, one of the most important issues in IR consists in the corpus vocabular...