The problem of learning a sparse conic combination of kernel functions or kernel matrices for classification or regression can be achieved via the regularization by a block 1-norm...
Francis R. Bach, Romain Thibaux, Michael I. Jordan
We present the preliminary design for a C++ template library to enable the compositional construction of matrix classes suitable for high performance numerical linear algebra comp...
Co-clustering can be viewed as a two-way (bilinear) factorization of a large data matrix into dense/uniform and possibly overlapping submatrix factors (co-clusters). This combinat...
Hao Zhu, Gonzalo Mateos, Georgios B. Giannakis, Ni...
Finding the sparsest solution for an under-determined linear system of equations D = s is of interest in many applications. This problem is known to be NP-hard. Recent work studie...
Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...