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AUSAI
2008
Springer
13 years 11 months ago
Using Gaussian Processes to Optimize Expensive Functions
The task of finding the optimum of some function f(x) is commonly accomplished by generating and testing sample solutions iteratively, choosing each new sample x heuristically on t...
Marcus R. Frean, Phillip Boyle
DCC
2008
IEEE
13 years 10 months ago
The Quadratic Gaussian Rate-Distortion Function for Source Uncorrelated Distortions
We characterize the rate-distortion function for zero-mean stationary Gaussian sources under the MSE fidelity criterion and subject to the additional constraint that the distortio...
Milan S. Derpich, Jan Østergaard, Graham C....
NIPS
2008
13 years 10 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
NIPS
2008
13 years 10 months ago
Sparse Convolved Gaussian Processes for Multi-output Regression
We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...
Mauricio Alvarez, Neil D. Lawrence
NIPS
2007
13 years 10 months ago
Inferring Neural Firing Rates from Spike Trains Using Gaussian Processes
Neural spike trains present challenges to analytical efforts due to their noisy, spiking nature. Many studies of neuroscientific and neural prosthetic importance rely on a smooth...
John P. Cunningham, Byron M. Yu, Krishna V. Shenoy...