Sciweavers

218 search results - page 11 / 44
» Simplifying mixture models through function approximation
Sort
View
CIG
2005
IEEE
14 years 1 months ago
Nannon: A Nano Backgammon for Machine Learning Research
A newly designed game is introduced, which feels like Backgammon, but has a simplified rule set. Unlike earlier attempts at simplifying the game, Nannon maintains enough features a...
Jordan B. Pollack
ROCAI
2004
Springer
14 years 28 days ago
Learning Mixtures of Localized Rules by Maximizing the Area Under the ROC Curve
We introduce a model class for statistical learning which is based on mixtures of propositional rules. In our mixture model, the weight of a rule is not uniform over the entire ins...
Tobias Sing, Niko Beerenwinkel, Thomas Lengauer
JCC
2002
73views more  JCC 2002»
13 years 7 months ago
Linear scaling approaches to quantum macromolecular similarity: Evaluating the similarity function
: The evaluation of the electron density based similarity function scales quadratically with respect to the size of the molecules for simplified, atomic shell densities. Due to the...
Pere Constans
ISBI
2006
IEEE
14 years 1 months ago
Shape analysis using the Fisher-Rao Riemannian metric: unifying shape representation and deformation
— We show that the Fisher-Rao Riemannian metric is a natural, intrinsic tool for computing shape geodesics. When a parameterized probability density function is used to represent...
Adrian Peter, Anand Rangarajan
COLT
2010
Springer
13 years 5 months ago
Toward Learning Gaussian Mixtures with Arbitrary Separation
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Mikhail Belkin, Kaushik Sinha