The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

The concave-convex procedure (CCCP) is a majorization-minimization algorithm that solves
dc (difference of convex functions) programs as a sequence of convex programs. In machine …

The concave-convex procedure (CCCP) is a majorization-minimization algorithm that solves
dc (difference of convex functions) programs as a sequence of convex programs. In machine …

Majorization methods solve minimization problems by replacing a complicated problem by a
sequence of simpler problems. Solving the sequence of simple optimization problems …

Bayesian Missing Data Problems: EM, Data Augmentation and Noniterative Computation
presents solutions to missing data problems through explicit or noniterative sampling …

The computation of robust regression estimates often relies on minimization of a convex
functional on a convex set. In this paper we discuss a general technique for a large class of …

It is well known that the bridge regression (with tuning parameter less or equal to 1) gives
asymptotically unbiased estimates of the nonzero regression parameters while shrinking …

In this paper, we consider the sparse eigenvalue problem wherein the goal is to obtain a
sparse solution to the generalized eigenvalue problem. We achieve this by constraining the …

In this paper, we consider the sparse eigenvalue problem wherein the goal is to obtain a
sparse solution to the generalized eigenvalue problem. We achieve this by constraining the …

De nos jours, les propriétés sensorielles des matériaux font l'objet d'une attention croissante
tant au point de vue hédonique qu'utilitaire. Notre thèse s' inscrit dans une recherche visant …