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...
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
This paper extends our previous work on feature transformationbased support vector machines for speaker recognition by proposing a joint MAP adaptation of feature transformation (...
We model the performance of a speaker recognition system used for surveillance to prioritize a large number of candidate speakers in search of a single target speaker. It is assum...
In this paper, we propose a practical object recognition system which consists of two functional modules. The first is object extraction module using a range image, and the second...