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» On Fitting Mixture Models
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NIPS
2001
15 years 5 months ago
Infinite Mixtures of Gaussian Process Experts
We present an extension to the Mixture of Experts (ME) model, where the individual experts are Gaussian Process (GP) regression models. Using an input-dependent adaptation of the ...
Carl Edward Rasmussen, Zoubin Ghahramani
ICDM
2005
IEEE
185views Data Mining» more  ICDM 2005»
15 years 10 months ago
Semi-Supervised Mixture of Kernels via LPBoost Methods
We propose an algorithm to construct classification models with a mixture of kernels from labeled and unlabeled data. The derived classifier is a mixture of models, each based o...
Jinbo Bi, Glenn Fung, Murat Dundar, R. Bharat Rao
CORR
2010
Springer
114views Education» more  CORR 2010»
15 years 4 months ago
Settling the Polynomial Learnability of Mixtures of Gaussians
Given data drawn from a mixture of multivariate Gaussians, a basic problem is to accurately estimate the mixture parameters. We give an algorithm for this problem that has running ...
Ankur Moitra, Gregory Valiant
ICDM
2007
IEEE
289views Data Mining» more  ICDM 2007»
15 years 10 months ago
Latent Dirichlet Conditional Naive-Bayes Models
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
Arindam Banerjee, Hanhuai Shan
NIPS
2001
15 years 5 months ago
Model Based Population Tracking and Automatic Detection of Distribution Changes
Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
Igor V. Cadez, Paul S. Bradley