We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...
Biological research is becoming increasingly complex and data-rich, with multiple public databases providing a variety of resources: hundreds of thousands of substances and interac...
Michael L. Blinov, Oliver Ruebenacker, James C. Sc...
In this paper, we present a systems approach for channel modeling of an Automatic Speech Recognition (ASR) system. This can have implications in improving speech recognition compo...
Qun Feng Tan, Kartik Audhkhasi, Panayiotis G. Geor...
Lack of realistic benchmarks hinders efficient design and evaluation of analysis techniques for feature models. We extract a variability model from the code base of the Linux kerne...
Steven She, Rafael Lotufo, Thorsten Berger, Andrze...
We present an initial investigation into the acoustic realisation of tone in continuous utterances in Sepedi (a language in the Southern Bantu family). An analytic model for the g...