This paper exploits recent developments in sparse approximation and compressive sensing to efficiently perform localization in a sensor network. We introduce a Bayesian framework...
Volkan Cevher, Petros Boufounos, Richard G. Barani...
Traditional machine learning algorithms assume that data are exact or precise. However, this assumption may not hold in some situations because of data uncertainty arising from mea...
Jiangtao Ren, Sau Dan Lee, Xianlu Chen, Ben Kao, R...
We propose Markov chain Monte Carlo sampling methods to address uncertainty estimation in disparity computation. We consider this problem at a postprocessing stage, i.e. once the d...
— This paper presents Natural Evolution Strategies (NES), a novel algorithm for performing real-valued ‘black box’ function optimization: optimizing an unknown objective func...
—In this paper we present a PDA-based fetal heart monitor that is able to provide instantaneous fetal heart rate (FHR) for the pregnant women. A modified spectral subtraction alg...
Jianfeng Chen, Koksoon Phua, Ying Song, Louis Shue