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INTERSPEECH
2010
15 years 20 days ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang
ECCV
2002
Springer
16 years 7 months ago
Multi-scale EM-ICP: A Fast and Robust Approach for Surface Registration
We investigate in this article the rigid registration of large sets of points, generally sampled from surfaces. We formulate this problem as a general Maximum-Likelihood (ML) estim...
Sébastien Granger, Xavier Pennec
ICDM
2010
IEEE
160views Data Mining» more  ICDM 2010»
15 years 3 months ago
A Privacy Preserving Framework for Gaussian Mixture Models
Abstract--This paper presents a framework for privacypreserving Gaussian Mixture Model computations. Specifically, we consider a scenario where a central service wants to learn the...
Madhusudana Shashanka
ICML
2006
IEEE
16 years 6 months ago
Convex optimization techniques for fitting sparse Gaussian graphical models
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
BMCBI
2007
109views more  BMCBI 2007»
15 years 6 months ago
A cis-regulatory logic simulator
Background: A major goal of computational studies of gene regulation is to accurately predict the expression of genes based on the cis-regulatory content of their promoters. The d...
Robert D. Zeigler, Jason Gertz, Barak A. Cohen