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Book
778views
17 years 23 days ago
Gaussian Processes for Machine Learning
"Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning...
Carl Edward Rasmussen and Christopher K. I. Willia...
128
Voted
ICPR
2006
IEEE
16 years 3 months ago
Statistical Model for the Classification of the Wavelet Transforms of T-ray Pulses
This study applies Auto Regressive (AR) and Auto Regressive Moving Average (ARMA) modeling to wavelet decomposed terahertz pulsed signals to assist biomedical diagnosis and mail/p...
Bradley Ferguson, Brian Wai-Him Ng, Derek Abbott, ...
128
Voted
KDD
2004
ACM
179views Data Mining» more  KDD 2004»
16 years 3 months ago
1-dimensional splines as building blocks for improving accuracy of risk outcomes models
Transformation of both the response variable and the predictors is commonly used in fitting regression models. However, these transformation methods do not always provide the maxi...
David S. Vogel, Morgan C. Wang
ICRA
2008
IEEE
150views Robotics» more  ICRA 2008»
15 years 9 months ago
A Bayesian approach to empirical local linearization for robotics
— Local linearizations are ubiquitous in the control of robotic systems. Analytical methods, if available, can be used to obtain the linearization, but in complex robotics system...
Jo-Anne Ting, Aaron D'Souza, Sethu Vijayakumar, St...
138
Voted
IJCNN
2008
IEEE
15 years 9 months ago
Two-level clustering approach to training data instance selection: A case study for the steel industry
— Nowadays, huge amounts of information from different industrial processes are stored into databases and companies can improve their production efficiency by mining some new kn...
Heli Koskimäki, Ilmari Juutilainen, Perttu La...