logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

On finding global optima for the hinge fitting problem

delete2004-01-01
delete1
delete
OA
AI
M
Marcelo Queiroz *
C
Carlos Humes
J
Joaquím J. Júdice
DOI：10.1016/S0305-0548(02)00179-Xdelete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
This paper considers the data fitting of n given points in R-m by a hinge function, as it appears in Breiman (IEEE Trans. Inform. Theory 39(3) (1993) 999) and Pucar and Sjoberg (IEEE Trans. Inform. Theory 44(3) (1998) 1310). This problem can be seen as a mathematical programming problem with a convex objective function and equilibrium constraints. For the euclidean error, an enumerative approach is proposed, which is a polynomial method in the sample size n, for a fixed dimension m. An alternative formulation for the 11 error is also introduced, which is processed by a Sequential Linear Complementarity Problem approach. Some numerical results with both algorithms are included to highlight the efficiency of those procedures.
Keywords:
least-squares problems
hinge functions
MPEC problems
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

C
Computers and Operations Research
IF:
4.3
Papers:
6.5K
Citations:
1.8W

Organization

No organization information available