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CEC
2011
IEEE
12 years 8 months ago
Stochastic Natural Gradient Descent by estimation of empirical covariances
—Stochastic relaxation aims at finding the minimum of a fitness function by identifying a proper sequence of distributions, in a given model, that minimize the expected value o...
Luigi Malagò, Matteo Matteucci, Giovanni Pi...
ICASSP
2011
IEEE
13 years 13 days ago
Stochastic resource allocation for cognitive radio networks based on imperfect state information
Efficient design of cognitive radio networks calls for secondary users implementing adaptive resource allocation, which requires knowledge of the channel state information in ord...
Antonio G. Marqués, Georgios B. Giannakis, ...
EMMCVPR
2005
Springer
14 years 2 months ago
Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering
This paper addresses the problem of efficient information theoretic, non-parametric data clustering. We develop a procedure for adapting the cluster memberships of the data pattern...
Robert Jenssen, Deniz Erdogmus, Kenneth E. Hild II...
JGTOOLS
2006
111views more  JGTOOLS 2006»
13 years 8 months ago
Stochastic Billboard Clouds for Interactive Foliage Rendering
We render tree foliage levels of detail (LODs) using a new adaptation of billboard clouds. Our contributions are a simple and efficient billboard cloud creation algorithm designed...
J. Dylan Lacewell, David Edwards, Peter Shirley, W...
ICML
1999
IEEE
14 years 9 months ago
Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Sebastian Thrun, John Langford, Dieter Fox