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» Using Gaussian Processes to Optimize Expensive Functions
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UAI
2008
13 years 9 months ago
Modelling local and global phenomena with sparse Gaussian processes
Much recent work has concerned sparse approximations to speed up the Gaussian process regression from the unfavorable O(n3 ) scaling in computational time to O(nm2 ). Thus far, wo...
Jarno Vanhatalo, Aki Vehtari
ICPR
2004
IEEE
14 years 8 months ago
Gaussian Energy Functions for Registration without Correspondences
A new criterion based on Gaussian fields is introduced and applied to the task of automatic rigid registration of point-sets. The method defines a simple energy function, which is...
Andreas Koschan, Besma R. Abidi, Faysal Boughorbel...
BMCBI
2008
228views more  BMCBI 2008»
13 years 7 months ago
Adaptive diffusion kernel learning from biological networks for protein function prediction
Background: Machine-learning tools have gained considerable attention during the last few years for analyzing biological networks for protein function prediction. Kernel methods a...
Liang Sun, Shuiwang Ji, Jieping Ye
CORR
2006
Springer
95views Education» more  CORR 2006»
13 years 7 months ago
Optimal Distortion-Power Tradeoffs in Gaussian Sensor Networks
We investigate the optimal performance of dense sensor networks by studying the joint source-channel coding problem. The overall goal of the sensor network is to take measurements ...
Nan Liu, Sennur Ulukus
ICML
2007
IEEE
14 years 8 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann