Abstract— In Evolutionary Robotics (ER), explicitly rewarding for behavioral diversity recently revealed to generate efficient results without recourse to complex fitness funct...
Abstract. Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the re...
Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, ...
Several types of low power passive equalizer is proposed and optimized in this work. The equalizer topologies include T-junction, parallel R-C and series R-L structures. These str...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Hidden Markov Model (HMM) is the dominant technology in speech recognition. The problem of optimizing model parameters is of great interest to the researchers in this area. The Ba...