A Predictor-Corrector Affine Scaling Method to Train Optimized Extreme Learning Machine

2021 ◽  
Author(s):  
Xiaojian Ding ◽  
Sheng Jin ◽  
Ming Lei ◽  
Fan Yang
Keyword(s):  
Extreme Learning Machine ◽  
Affine Scaling ◽  
Scaling Method ◽  
Learning Machine ◽  
Affine Scaling Method ◽  
Predictor Corrector

scholarly journals On the relationship of interior-point methods

1993 ◽  
Vol 16 (3) ◽  
pp. 565-572
Author(s):  
Ruey-Lin Sheu ◽  
Shu-Cherng Fang
Keyword(s):  
Interior Point ◽  
Barrier Function ◽  
Affine Scaling ◽  
Logarithmic Barrier Function ◽  
Scaling Method ◽  
Dual Affine ◽  
Primal Dual ◽  
Affine Scaling Method ◽  
Relationship Of ◽  
Logarithmic Barrier

In this paper, we show that the moving directions of the primal-affine scaling method (with logarithmic barrier function), the dual-affine scaling method (with logarithmic barrier function), and the primal-dual interior point method are merely the Newton directions along three different algebraic “paths” that lead to a solution of the Karush-Kuhn-Tucker conditions of a given linear programming problem. We also derive the missing dual information in the primal-affine scaling method and the missing primal information in the dual-affine scaling method. Basically, the missing information has the same form as the solutions generated by the primal-dual method but with different scaling matrices.

A primal null-space affine-scaling method

1994 ◽  
Vol 20 (3) ◽  
pp. 373-392 ◽  
Author(s):  
K. Kim ◽  
J. L. Nazareth
Keyword(s):  
Null Space ◽  
Affine Scaling ◽  
Scaling Method ◽  
Affine Scaling Method
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