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.
|出版ステータス||Published - 2011 12月 1|
|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月 18 → 2011 10月 21
|Other||Asia-Pacific Signal and Information Processing Association Annual Summit and Conference 2011, APSIPA ASC 2011|
|Period||11/10/18 → 11/10/21|
ASJC Scopus subject areas