On extensions of LARS by information geometry: Convex objectives and ̀p-norm

Masahiro Yukawa, Shun Ichi Amari

研究成果: Paper査読

2 被引用数 (Scopus)

抄録

This paper addresses extensions of the Least Angle Regression (LARS) algorithm from two different aspects: (i) from quadratic to more general objectives, and (ii) from ̀1-norm to ̀p-norm for p < 1. The equiangular vector, which is the key of LARS, is reproduced in connection with the Riemannian metric induced by the objective function, thereby making the extensions feasible. It is shown, in the case of p < 1, that two types of trajectory . the c-trajectory and the λ-trajectory . need to be distinguished by revealing the discontinuity of the λ-trajectory.

本文言語English
ページ326-331
ページ数6
出版ステータスPublished - 2011 12 1
外部発表はい
イベントAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011 - Xi'an, China
継続期間: 2011 10 182011 10 21

Other

OtherAsia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011
CountryChina
CityXi'an
Period11/10/1811/10/21

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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