Manymethods for analyzing biological problems are constrained by problemsize. Theability to distinguish betweenrelevant andirrelevant features of a problemmay allowa problemto be ...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
In this letter, a novel modular neural network (MNN) classifier, which partitions a K-class problem into many much easier two-class problems in sub-subspaces, was proposed to per...
In this paper, we present a novel multi-modal histogram thresholding method in which no a priori knowledge about the number of clusters to be extracted is needed. The proposed met...
This paper proposes a novel framework for automatic text categorization problem based on the kernel density classifier. The overall goal is to tackle two main issues in automatic ...
Dwi Sianto Mansjur, Ted S. Wada, Biing-Hwang Juang