We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Suppose a set of images contains frequent occurrences of objects from an unknown category. This paper is aimed at simultaneously solving the following related problems: (1) unsupe...
Abstract--This paper presents a new wavelet-based image denoising method, which extends a recently emerged "geometrical" Bayesian framework. The new method combines three...
Aleksandra Pizurica, Wilfried Philips, Ignace Lema...
In this paper, we present several novel strategies to improve software controlled cache utilization, so as to achieve lower power requirements for multi-media and signal processin...
—A cardinal prerequisite for the system design of a sensor network, is to understand the geometric environment where sensor nodes are deployed. The global topology of a largescal...