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» Hierarchical Gaussian Process Regression
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NIPS
2004
13 years 6 months ago
Learning Gaussian Process Kernels via Hierarchical Bayes
We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are l...
Anton Schwaighofer, Volker Tresp, Kai Yu
JMLR
2010
141views more  JMLR 2010»
12 years 11 months ago
Hierarchical Gaussian Process Regression
We address an approximation method for Gaussian process (GP) regression, where we approximate covariance by a block matrix such that diagonal blocks are calculated exactly while o...
Sunho Park, Seungjin Choi
CEC
2005
IEEE
13 years 10 months ago
A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary alg
This paper presents a study on Hierarchical Surrogate-Assisted Evolutionary Algorithm (HSAEA) using different global surrogate models for solving computationally expensive optimiza...
Zongzhao Zhou, Yew-Soon Ong, My Hanh Nguyen, Dudy ...
BMCBI
2011
12 years 8 months ago
A Simple Approach to Ranking Differentially Expressed Gene Expression Time Courses through Gaussian Process Regression
Background: The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) ...
Alfredo A. Kalaitzis, Neil D. Lawrence
JMLR
2010
118views more  JMLR 2010»
12 years 11 months ago
Gaussian processes with monotonicity information
A method for using monotonicity information in multivariate Gaussian process regression and classification is proposed. Monotonicity information is introduced with virtual derivat...
Jaakko Riihimäki, Aki Vehtari