We consider a general class of regularization methods which learn a vector of parameters on the basis of linear measurements. It is well known that if the regularizer is a nondecr...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
We study the problem of covering a set of points or polyhedra in 3 with two axis-aligned boxes in order to minimize a function of the measures of the two boxes, such as the sum or...
Esther M. Arkin, Gill Barequet, Joseph S. B. Mitch...
In this work we study a wide range of online and offline routing and packing problems with various objectives. We provide a unified approach, based on a clean primal-dual method...
eresting web-available abstracts and papers on clustering: An Analysis of Recent Work on Clustering Algorithms (1999), Daniel Fasulo : This paper describes four recent papers on cl...
Abstract. Maximum likelihood (ML) is an increasingly popular optimality criterion for selecting evolutionary trees [Felsenstein 1981]. Finding optimal ML trees appears to be a very...