Traditional feature selection methods assume that the data are independent and identically distributed (i.i.d.). In real world, tremendous amounts of data are distributed in a net...
In this paper we propose a general framework to solve the articulated shape matching problem, formulated as finding point-to-point correspondences between two shapes represented b...
Diana Mateus, Fabio Cuzzolin, Radu Horaud, Edmond ...
Fisher score and Laplacian score are two popular feature selection algorithms, both of which belong to the general graph-based feature selection framework. In this framework, a fe...
Feiping Nie, Shiming Xiang, Yangqing Jia, Changshu...
In this paper, we present a series of distributed algorithms for coverage verification in sensor networks with no location information. We demonstrate how, in the absence of locali...
Many problems in information processing involve some form of dimensionality reduction. In this paper, we introduce Locality Preserving Projections (LPP). These are linear projecti...