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» Approximating Component Selection
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NPL
2006
100views more  NPL 2006»
13 years 7 months ago
Constrained Projection Approximation Algorithms for Principal Component Analysis
Abstract. In this paper we introduce a new error measure, integrated reconstruction error (IRE) and show that the minimization of IRE leads to principal eigenvectors (without rotat...
Seungjin Choi, Jong-Hoon Ahn, Andrzej Cichocki
NPL
2008
63views more  NPL 2008»
13 years 7 months ago
New Routes from Minimal Approximation Error to Principal Components
We introduce two new methods of deriving the classical PCA in the framework of minimizing the mean square error upon performing a lower-dimensional approximation of the data. These...
Abhilash Alexander Miranda, Yann-Aël Le Borgn...
ESANN
2006
13 years 8 months ago
On the selection of hidden neurons with heuristic search strategies for approximation
Abstract. Feature Selection techniques usually follow some search strategy to select a suitable subset from a set of features. Most neural network growing algorithms perform a sear...
Ignacio Barrio, Enrique Romero, Lluís A. Be...
SIGMOD
2003
ACM
172views Database» more  SIGMOD 2003»
14 years 7 months ago
Dynamic Sample Selection for Approximate Query Processing
In decision support applications, the ability to provide fast approximate answers to aggregation queries is desirable. One commonly-used technique for approximate query answering ...
Brian Babcock, Surajit Chaudhuri, Gautam Das