Nearest neighbor (NN) classification assumes locally constant class conditional probabilities, and suffers from bias in high dimensions with a small sample set. In this paper, we p...
Traditional parallel compilers do not effectively parallelize irregular applications because they contain little looplevel parallelism due to ambiguous memory references. We explo...
One of the intrinsic problems of mobility in wireless networks is the discovery of mobile nodes. A widely used solution for this problem is to use different variations of beacons, ...
Existing sequential feature-based registration algorithms involving search typically either select features randomly (eg. the RANSAC[8] approach) or assume a predefined, intuitive...
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...