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TSP
2008
89views more  TSP 2008»
13 years 5 months ago
The Kernel Least-Mean-Square Algorithm
The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample by sample update for an adaptive filter in reproducing Kernel Hil...
Weifeng Liu, Puskal P. Pokharel, Jose C. Principe
PAMI
2012
11 years 7 months ago
A Least-Squares Framework for Component Analysis
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Fernando De la Torre
COLT
2006
Springer
13 years 7 months ago
Can Entropic Regularization Be Replaced by Squared Euclidean Distance Plus Additional Linear Constraints
There are two main families of on-line algorithms depending on whether a relative entropy or a squared Euclidean distance is used as a regularizer. The difference between the two f...
Manfred K. Warmuth
GECCO
2008
Springer
172views Optimization» more  GECCO 2008»
13 years 6 months ago
Recursive least squares and quadratic prediction in continuous multistep problems
XCS with computed prediction, namely XCSF, has been recently extended in several ways. In particular, a novel prediction update algorithm based on recursive least squares and the ...
Daniele Loiacono, Pier Luca Lanzi
CORR
2008
Springer
216views Education» more  CORR 2008»
13 years 5 months ago
Building an interpretable fuzzy rule base from data using Orthogonal Least Squares Application to a depollution problem
In many fields where human understanding plays a crucial role, such as bioprocesses, the capacity of extracting knowledge from data is of critical importance. Within this framewor...
Sébastien Destercke, Serge Guillaume, Brigi...