Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
This paper presents an efficient implementation of a robust adaptive beamforming algorithm based on convex optimization for applications in the processing-constrained environment...
Eric A. Durant, Ivo Merks, Bill Woods, Jinjun Xiao...
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
We address the blind source separation (BSS) problem for the convolutive mixing case. Second-order statistical methods are employed assuming the source signals are non-stationary a...
Efficient Natural Evolution Strategies (eNES) is a novel alternative to conventional evolutionary algorithms, using the natural gradient to adapt the mutation distribution. Unlike...