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» Using Gaussian Processes to Optimize Expensive Functions
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NIPS
2001
13 years 8 months ago
Learning a Gaussian Process Prior for Automatically Generating Music Playlists
This paper presents AutoDJ: a system for automatically generating music playlists based on one or more seed songs selected by a user. AutoDJ uses Gaussian Process Regression to le...
John C. Platt, Christopher J. C. Burges, S. Swenso...
NIPS
2008
13 years 9 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
JMLR
2010
125views more  JMLR 2010»
13 years 2 months ago
Regret Bounds for Gaussian Process Bandit Problems
Bandit algorithms are concerned with trading exploration with exploitation where a number of options are available but we can only learn their quality by experimenting with them. ...
Steffen Grünewälder, Jean-Yves Audibert,...
CVPR
2008
IEEE
13 years 9 months ago
Probabilistic multi-tensor estimation using the Tensor Distribution Function
Diffusion weighted magnetic resonance (MR) imaging is a powerful tool that can be employed to study white matter microstructure by examining the 3D displacement profile of water m...
Alex D. Leow, Siwei Zhu, Katie McMahon, Greig I. d...
ICML
2004
IEEE
14 years 8 months ago
Parameter space exploration with Gaussian process trees
Computer experiments often require dense sweeps over input parameters to obtain a qualitative understanding of their response. Such sweeps can be prohibitively expensive, and are ...
Robert B. Gramacy, Herbert K. H. Lee, William G. M...