We develop a computationally efficient and memory efficient approach to (near) maximum a posteriori probability demodulation for MIMO systems with QPSK signalling, based on semi...
Mehran Nekuii, Mikalai Kisialiou, Timothy N. David...
Consider the problem of signal detection via multiple distributed noisy sensors. We propose a linear decision fusion rule to combine the local statistics from individual sensors i...
The problem of computing approximate GCDs of several polynomials with real or complex coefficients can be formulated as computing the minimal perturbation such that the perturbed ...
Given a set of patterns and a similarity measure between them, we will present an optimization framework to approximate a small subset, known as a canonical set, whose members clo...
In this paper, we present a novel semidefinite programming approach for multiple-instance learning. We first formulate the multipleinstance learning as a combinatorial maximum marg...