Abstract -We study the problem of communication reliability and diversity in multi-hop wireless networks. Our aim is to develop a new network model that better takes into account t...
Amir Ehsan Khandani, Jinane Abounadi, Eytan Modian...
Approximate Bayesian Gaussian process (GP) classification techniques are powerful nonparametric learning methods, similar in appearance and performance to support vector machines....
Abstract. We analyze the computational complexity of various twodimensional platform games. We identify common properties of these games that allow us to state several meta-theorem...
Background: RNA structure prediction problem is a computationally complex task, especially with pseudo-knots. The problem is well-studied in existing literature and predominantly ...
S. P. T. Krishnan, Sim Sze Liang, Bharadwaj Veerav...
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropr...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...