We present a new semi-supervised training procedure for conditional random fields (CRFs) that can be used to train sequence segmentors and labelers from a combination of labeled a...
Feng Jiao, Shaojun Wang, Chi-Hoon Lee, Russell Gre...
The purpose of this paper is to advocate and encourage the application of fuzzy-neuro algorithms in the risk assessment of Distributed Real-Time (DRT) systems, where object-orient...
The paper introduces mixed networks, a new framework for expressing and reasoning with probabilistic and deterministic information. The framework combines belief networks with con...
Heuristics used by search algorithms are usually composed of more primitive functions which we call "features". A method for combining features is presented which is bas...
: Boosting is a general method for improving the accuracy of any given learning algorithm. In this paper we employ combination of Adaboost with Support Vector Machine (SVM) as comp...