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CEC
2005
IEEE
14 years 2 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 ...
SDM
2008
SIAM
144views Data Mining» more  SDM 2008»
13 years 10 months ago
Active Learning with Model Selection in Linear Regression
Optimally designing the location of training input points (active learning) and choosing the best model (model selection) are two important components of supervised learning and h...
Masashi Sugiyama, Neil Rubens
DAGM
2010
Springer
13 years 10 months ago
Local Regression Based Statistical Model Fitting
Fitting statistical models is a widely employed technique for the segmentation of medical images. While this approach gives impressive results for simple structures, shape models a...
Matthias Amberg, Marcel Lüthi, Thomas Vetter
ISNN
2005
Springer
14 years 2 months ago
Support Vector Regression for Software Reliability Growth Modeling and Prediction
In this work, we propose to apply support vector regression (SVR) to build software reliability growth model (SRGM). SRGM is an important aspect in software reliability engineering...
Fei Xing, Ping Guo
ECML
2006
Springer
14 years 16 days ago
Transductive Gaussian Process Regression with Automatic Model Selection
Abstract. In contrast to the standard inductive inference setting of predictive machine learning, in real world learning problems often the test instances are already available at ...
Quoc V. Le, Alexander J. Smola, Thomas Gärtne...