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ICCV
2009
IEEE
14 years 11 months ago
Bayesian Poisson regression for crowd counting
Poisson regression models the noisy output of a counting function as a Poisson random variable, with a log-mean parameter that is a linear function of the input vector. In this wo...
Antoni B. Chan, Nuno Vasconcelos
BMCBI
2007
194views more  BMCBI 2007»
15 years 1 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
ICASSP
2011
IEEE
14 years 4 months ago
Stochastic transceiver design in multi-antenna channels with statistical channel state information
The problem of stochastic robust sum mean square error (MSE) minimization transceiver design is addressed for multiple-input multiple-output (MIMO) broadcast channels (BCs). The t...
Andreas Gründinger, Michael Joham, Wolfgang U...
BMVC
2010
14 years 11 months ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata
TIT
2008
95views more  TIT 2008»
15 years 1 months ago
Mutual Information and Conditional Mean Estimation in Poisson Channels
Abstract--Following the discovery of a fundamental connection between information measures and estimation measures in Gaussian channels, this paper explores the counterpart of thos...
Dongning Guo, Shlomo Shamai, Sergio Verdú