ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
We propose a novel semi-supervised method for building a statistical model that represents the relationship between sounds and text labels (“tags”). The proposed method, named...
TEC
2010
13 years 2 months ago
2010
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
JMLR
2010
13 years 2 months ago
2010
Estimating the conditional mean of an inputoutput relation is the goal of regression. However, regression analysis is not sufficiently informative if the conditional distribution ...
EJASP
2010
13 years 2 months ago
2010
Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density esti...
NECO
2011
13 years 2 months ago
2011
Accurately evaluating statistical independence among random variables is a key element of Independent Component Analysis (ICA). In this paper, we employ a squared-loss variant of ...
COLT
2010
Springer
13 years 5 months ago
2010
Springer
We study graph estimation and density estimation in high dimensions, using a family of density estimators based on forest structured undirected graphical models. For density estim...
IVC
2010
13 years 6 months ago
2010
In this paper we propose a Gaussian-kernel-based online kernel density estimation which can be used for applications of online probability density estimation and online learning. ...
PRL
2007
13 years 7 months ago
2007
We present a method for initialising the K-means clustering algorithm. Our method hinges on the use of a kd-tree to perform a density estimation of the data at various locations. ...
ML
2007
ACM
13 years 7 months ago
2007
ACM
We consider multivariate density estimation with identically distributed observations. We study a density estimator which is a convex combination of functions in a dictionary and ...
CGF
2007
13 years 7 months ago
2007
We present a novel framework for efficiently computing the indirect illumination in diffuse and moderately glossy scenes using density estimation techniques. Many existing global...