The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
The recent years have witnessed a surge of interests in Nonnegative Matrix Factorization (NMF) in data mining and machine learning fields. Despite its elegant theory and empirical...
The stability of low-rank matrix reconstruction is investigated in this paper. The -constrained minimal singular value ( -CMSV) of the measurement operator is shown to determine t...
In this paper, a new adaptive beamforming algorithm with joint robustness against covariance matrix uncertainty as well as steering vector mismatch is proposed. First, the theoret...
A hardware ef cient approach is introduced for elementary function evaluations in certain structured matrix computations. It is a comprehensive approach that utilizes lookup table...