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» Dimension Reduction for Regression with Bottleneck Neural Ne...
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NIPS
2003
13 years 9 months ago
Nonstationary Covariance Functions for Gaussian Process Regression
We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smo...
Christopher J. Paciorek, Mark J. Schervish
DMIN
2006
124views Data Mining» more  DMIN 2006»
13 years 9 months ago
Optimal Multi-class Classification with Principal Components
An approach to build a multi-class classifier is proposed in this paper. This approach consists of a derivation to show under which loss function an optimal classifier can be obtai...
Albert Hoang
IJCINI
2007
125views more  IJCINI 2007»
13 years 7 months ago
A Unified Approach To Fractal Dimensions
The Cognitive Processes of Abstraction and Formal Inferences J. A. Anderson: A Brain-Like Computer for Cognitive Software Applications: the Resatz Brain Project L. Flax: Cognitive ...
Witold Kinsner
FLAIRS
2004
13 years 9 months ago
Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ZhenQiu Liu, Dechang Chen
ICANN
2005
Springer
14 years 1 months ago
High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data
Multidimensional Scaling (MDS) is a powerful dimension reduction technique for embedding high-dimensional data into a lowdimensional target space. Thereby, the distance relationshi...
Marc Strickert, Stefan Teichmann, Nese Sreenivasul...