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UAI
2008
13 years 10 months ago
Projected Subgradient Methods for Learning Sparse Gaussians
Gaussian Markov random fields (GMRFs) are useful in a broad range of applications. In this paper we tackle the problem of learning a sparse GMRF in a high-dimensional space. Our a...
John Duchi, Stephen Gould, Daphne Koller
NIPS
2003
13 years 10 months ago
Gaussian Processes in Reinforcement Learning
We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
Carl Edward Rasmussen, Malte Kuss
NIPS
2003
13 years 10 months ago
GPPS: A Gaussian Process Positioning System for Cellular Networks
In this article, we present a novel approach to solving the localization problem in cellular networks. The goal is to estimate a mobile user’s position, based on measurements of...
Anton Schwaighofer, Marian Grigoras, Volker Tresp,...
NIPS
1998
13 years 10 months ago
Batch and On-Line Parameter Estimation of Gaussian Mixtures Based on the Joint Entropy
We describe a new iterative method for parameter estimation of Gaussian mixtures. The new method is based on a framework developed by Kivinen and Warmuth for supervised on-line le...
Yoram Singer, Manfred K. Warmuth
FSKD
2008
Springer
120views Fuzzy Logic» more  FSKD 2008»
13 years 10 months ago
An Unsupervised Gaussian Mixture Classification Mechanism Based on Statistical Learning Analysis
This paper presents a scheme for unsupervised classification with Gaussian mixture models by means of statistical learning analysis. A Bayesian Ying-Yang harmony learning system a...
Rui Nian, Guangrong Ji, Michel Verleysen