In this paper, we consider the problem of planning and learning in the infinite-horizon discounted-reward Markov decision problems. We propose a novel iterative direct policysearc...
Nowadays, object recognition is widely studied under the paradigm of matching local features. This work describes a genetic programming methodology that synthesizes mathematical e...
Wepropose in this paper a modularlearning environmentfor proteinmodeling.In this system,the protein modelingproblemis tackledin twosuccessive phases. First, partial structural inf...
This study examined the unique contribution of computer-based instruction when compared with more conventional modes of instruction (i.e. teacher instruction with textbooks) to ear...
Until recently, parallel programming has largely focused on the exploitation of data-parallelism in dense matrix programs. However, many important application domains, including m...
Milind Kulkarni, Martin Burtscher, Calin Cascaval,...