37 search results - page 1 / 8 » Toward Learning Gaussian Mixtures with Arbitrary Separation |
COLT
2010
Springer
13 years 2 months ago
2010
Springer
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...
FOCS
2005
IEEE
13 years 10 months ago
2005
IEEE
We consider the problem of learning mixtures of arbitrary symmetric distributions. We formulate sufficient separation conditions and present a learning algorithm with provable gua...
COLT
2005
Springer
13 years 10 months ago
2005
Springer
We consider the problem of learning mixtures of distributions via spectral methods and derive a tight characterization of when such methods are useful. Specifically, given a mixt...
CORR
2006
Springer
13 years 4 months ago
2006
Springer
Abstract. We propose and analyze a new vantage point for the learning of mixtures of Gaussians: namely, the PAC-style model of learning probability distributions introduced by Kear...
JAIR
1998
13 years 4 months ago
1998
This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...