We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. This problem can ...
The perplexing effects of noise and high feature dimensionality greatly complicate functional magnetic resonance imaging (fMRI) classification. In this paper, we present a novel f...
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
Short-range wireless audio transmission with high quality on the one hand often encounters error-prone channels, while on the other hand decoding delay plays a critical role in th...
The recent ubiquity of mobile telephony has posed the challenge of forensic speech analysis on compressed speech content. Whilst existing research studies have investigated the ef...