The Sparse Principal Component of a Constant-rank Matrix

no code implementations • 20 Dec 2013 • Megasthenis Asteris, Dimitris S. Papailiopoulos, George N. Karystinos

In this work, we prove that, if the matrix is positive semidefinite and its rank is constant, then its sparse principal component is polynomially computable.

Some Options for L1-Subspace Signal Processing

no code implementations • 4 Sep 2013 • Panos P. Markopoulos, George N. Karystinos, Dimitris A. Pados

We describe ways to define and calculate $L_1$-norm signal subspaces which are less sensitive to outlying data than $L_2$-calculated subspaces.

Dimensionality Reduction Direction of Arrival Estimation