In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
Surrogate maximization (or minimization) (SM) algorithms are a family of algorithms that can be regarded as a generalization of expectation-maximization (EM) algorithms. There are...
—Efficient channel feedback methods are becoming more important in limited-feedback multi-user multiple input multiple output (MU-MIMO) systems. We propose a new Dynamic channEl...
This short note studies a variation of the Compressed Sensing paradigm introduced recently by Vaswani et al., i.e. the recovery of sparse signals from a certain number of linear m...
We present a simple, accurate, and flexible method to calibrate intrinsic parameters of a camera together with (possibly significant) lens distortion. This new method can work u...