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» A Stagewise Least Square Loss Function for Classification
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SDM
2008
SIAM
150views Data Mining» more  SDM 2008»
13 years 6 months ago
A Stagewise Least Square Loss Function for Classification
This paper presents a stagewise least square (SLS) loss function for classification. It uses a least square form within each stage to approximate a bounded monotonic nonconvex los...
Shuang-Hong Yang, Bao-Gang Hu
IJCNN
2006
IEEE
13 years 10 months ago
On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning
— We present a simple, intuitive argument based on “invariant imbedding” in the spirit of dynamic programming to derive a stagewise second-order backpropagation (BP) algorith...
Eiji Mizutani, Stuart Dreyfus
FOCM
2006
97views more  FOCM 2006»
13 years 4 months ago
Learning Rates of Least-Square Regularized Regression
This paper considers the regularized learning algorithm associated with the leastsquare loss and reproducing kernel Hilbert spaces. The target is the error analysis for the regres...
Qiang Wu, Yiming Ying, Ding-Xuan Zhou
ICPR
2008
IEEE
13 years 11 months ago
A least square kernel machine with box constraints
In this paper, we present a least square kernel machine with box constraints (LSKMBC). The existing least square machines assume Gaussian hyperpriors and subsequently express the ...
Jayanta Basak
TIT
2002
89views more  TIT 2002»
13 years 4 months ago
Universal linear least squares prediction: Upper and lower bounds
We consider the problem of sequential linear prediction of real-valued sequences under the square-error loss function. For this problem, a prediction algorithm has been demonstrate...
Andrew C. Singer, Suleyman Serdar Kozat, Meir Fede...