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NIPS
2007
13 years 9 months ago
Learning with Tree-Averaged Densities and Distributions
We utilize the ensemble of trees framework, a tractable mixture over superexponential number of tree-structured distributions [1], to develop a new model for multivariate density ...
Sergey Kirshner
SSPR
2010
Springer
13 years 5 months ago
Non-parametric Mixture Models for Clustering
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
Pavan Kumar Mallapragada, Rong Jin, Anil K. Jain
IJCV
2006
266views more  IJCV 2006»
13 years 7 months ago
Kernel Density Estimation and Intrinsic Alignment for Shape Priors in Level Set Segmentation
In this paper, we make two contributions to the field of level set based image segmentation. Firstly, we propose shape dissimilarity measures on the space of level set functions wh...
Daniel Cremers, Stanley Osher, Stefano Soatto
ICA
2004
Springer
14 years 26 days ago
Blind Maximum Likelihood Separation of a Linear-Quadratic Mixture
Abstract. We proposed recently a new method for separating linearquadratic mixtures of independent real sources, based on parametric identification of a recurrent separating struc...
Shahram Hosseini, Yannick Deville
ISCAS
2003
IEEE
99views Hardware» more  ISCAS 2003»
14 years 23 days ago
New hyperbolic source density models for blind source recovery score functions
We present two new hyperbolic source probability models to effectively represent sub-gaussian and super-gaussian families of sources for dynamic and convolutive Blind Source Recov...
Khurram Waheed, Fathi M. Salem