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» Multi-task Gaussian Process Prediction
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TEC
2010
129views more  TEC 2010»
13 years 1 months ago
Expensive Multiobjective Optimization by MOEA/D With Gaussian Process Model
In some expensive multiobjective optimization problems, several function evaluations can be carried out at one time. Therefore, it is very desirable to develop methods which can g...
Qingfu Zhang, Wudong Liu, Edward P. K. Tsang, Boto...
ESSMAC
2003
Springer
13 years 12 months ago
Analysis of Some Methods for Reduced Rank Gaussian Process Regression
Abstract. While there is strong motivation for using Gaussian Processes (GPs) due to their excellent performance in regression and classification problems, their computational com...
Joaquin Quiñonero Candela, Carl Edward Rasm...
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...
JMLR
2010
147views more  JMLR 2010»
13 years 1 months ago
Gaussian Processes for Machine Learning (GPML) Toolbox
The GPML toolbox provides a wide range of functionality for Gaussian process (GP) inference and prediction. GPs are specified by mean and covariance functions; we offer a library ...
Carl Edward Rasmussen, Hannes Nickisch
ICML
2004
IEEE
14 years 7 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...