BCS
2008
13 years 6 months ago
2008
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
AAAI
2007
13 years 6 months ago
2007
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a Reprod...
Publication
We present a class of models that, via a simple construction,
enables exact, incremental, non-parametric, polynomial-time,
Bayesian inference of conditional measures. The approac...
CIKM
2006
Springer
13 years 8 months ago
2006
Springer
A fundamental building block of many data mining and analysis approaches is density estimation as it provides a comprehensive statistical model of a data distribution. For that re...
CGI
2004
IEEE
13 years 8 months ago
2004
IEEE
Photon tracing and density estimation are well established techniques in global illumination computation and rendering of high-quality animation sequences. Using traditional densi...
ACIVS
2007
Springer
13 years 8 months ago
2007
Springer
Abstract. The first step in various computer vision applications is a detection of moving objects. The prevalent pixel-wise models regard image pixels as independent random process...
GFKL
2004
Springer
13 years 10 months ago
2004
Springer
Abstract. A method for measuring the density of data sets that contain an unknown number of clusters of unknown sizes is proposed. This method, called Pareto Density Estimation (PD...
DIS
2007
Springer
13 years 10 months ago
2007
Springer
We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a reprodu...
PG
2007
IEEE
13 years 10 months ago
2007
IEEE
Standard density estimation approaches suffer from visible bias due to low-pass filtering of the lighting function. Therefore, most photon density estimation methods have been us...
IDA
2009
Springer
13 years 11 months ago
2009
Springer
Abstract. Accurately evaluating statistical independence among random variables is a key component of Independent Component Analysis (ICA). In this paper, we employ a squared-loss ...