In this paper, we propose a semi-supervised kernel matching method to address domain adaptation problems where the source distribution substantially differs from the target distri...
One of the main shortcomings of Markov chain Monte Carlo samplers is their inability to mix between modes of the target distribution. In this paper we show that advance knowledge ...
Mismatch between training and test conditions deteriorates the performance of speech recognizers. This paper investigates the combination of parametric histogram equalization (pHE...
We address the problem of learning classifiers for several related tasks that may differ in their joint distribution of input and output variables. For each task, small
This paper presents a technique for efficiently generating random numbers from a given probability distribution. This is achieved by using a generic hardware architecture, which t...
Abstract— Particle Filters have been widely used as a powerful optimization tool for nonlinear, non-Gaussian dynamic models such as Simultaneous Localization and Mapping (SLAM) a...
In this paper, a novel method to extend the grayscale histogram equalization (GHE) for color images in a multidimension is proposed. Unlike most current techniques, the proposed m...