This paper presents a new partitioning algorithm to perform matrix multiplication on two interconnected heterogeneous processors. Data is partitioned in a way which minimizes the ...
As a well known fixed-point iteration algorithm for kernel
density mode-seeking, Mean-Shift has attracted wide attention
in pattern recognition field. To date, Mean-Shift algorit...
We present a polytope-kernel density estimation (PKDE) methodology that allows us to perform exact mean-shift updates along the edges of the Delaunay graph of the data. We discuss...
Kernel methods have been popular over the last decade to solve many computer vision, statistics and machine learning problems. An important, both theoretically and practically, op...
We consider clustering situations in which the pairwise affinity between data points depends on a latent ”context” variable. For example, when clustering features arising fro...