I discuss algorithms based on bistellar flips for inserting and deleting constraining (d − 1)-facets in d-dimensional constrained Delaunay triangulations (CDTs) and weighted CD...
In this paper, we study the problem of learning a matrix W from a set of linear measurements. Our formulation consists in solving an optimization problem which involves regulariza...
Andreas Argyriou, Charles A. Micchelli, Massimilia...
We propose a general and efficient algorithm for learning low-rank matrices. The proposed algorithm converges super-linearly and can keep the matrix to be learned in a compact fac...
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
This paper develops a classification algorithm in the framework of spectral graph theory where the underlying manifold of a high dimensional data set is described by a graph. The...