This paper proposes an image compression approach, in which we incorporate primal sketch based learning into the mainstream image compression framework. The key idea of our approa...
This paper focuses on agent-based approach to study the relationship between the individual behavior of participants and the overall development of a virtual community, to help pe...
We deploy a novel Reinforcement Learning optimization technique based on afterstates learning to determine the gain that can be achieved by incorporating movement prediction inform...
Abstract. The algorithm selection problem aims to select the best algorithm for an input problem instance according to some characteristics of the instance. This paper presents a l...
Abstract. This paper calls on activity theory as tool for analyzing Asynchronous Learning Networks (ALN) to achieve a better understanding of their dynamics. This paper makes some ...