Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...
This paper presents an adaptive discriminative generative model that generalizes the conventional Fisher Linear Discriminant algorithm and renders a proper probabilistic interpret...
Ruei-Sung Lin, David A. Ross, Jongwoo Lim, Ming-Hs...
Abstract-- Speaker space based adaptation methods for automatic speech recognition have been shown to provide significant performance improvements for tasks where only a few second...
We present a simple set of data structures, and a collection of methods for constructing and updating the structures, designed to support the use of cohesive elements in simulation...
Signal and image enhancement is considered in the context of a new type of diffusion process that simultaneously enhances, sharpens, and denoises images. The nonlinear diffusion co...