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» Semi-Supervised Learning of Mixture Models
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DSP
2007
15 years 2 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...
ACCV
2010
Springer
14 years 9 months ago
Latent Gaussian Mixture Regression for Human Pose Estimation
Discriminative approaches for human pose estimation model the functional mapping, or conditional distribution, between image features and 3D pose. Learning such multi-modal models ...
Yan Tian, Leonid Sigal, Hernán Badino, Fern...
133
Voted
ML
2000
ACM
157views Machine Learning» more  ML 2000»
15 years 2 months ago
A Multistrategy Approach to Classifier Learning from Time Series
We present an approach to inductive concept learning using multiple models for time series. Our objective is to improve the efficiency and accuracy of concept learning by decomposi...
William H. Hsu, Sylvian R. Ray, David C. Wilkins
COLT
2010
Springer
15 years 20 days 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
148
Voted
CVPR
2010
IEEE
15 years 2 months ago
Scene understanding by statistical modeling of motion patterns
We present a novel method for the discovery and statistical representation of motion patterns in a scene observed by a static camera. Related methods involving learning of pattern...
Imran Saleemi, Lance Hartung, Mubarak Shah