We present a novel approach to semisupervised learning which is based on statistical physics. Most of the former work in the field of semi-supervised learning classifies the point...
Abstract: Tomorrow’s embedded devices need to run high-resolution multimedia applications which need an enormous computational complexity with a very low energy consumption const...
In this paper, we present novel techniques that improve the computational and memory efficiency of algorithms for solving multi-label energy functions arising from discrete MRFs o...
Karteek Alahari, Pushmeet Kohli, Philip H. S. Torr
The development of energy-conscious embedded and/or mobile systems exposes a trade-off between energy consumption and system performance. Recent microprocessors have incorporated ...
Ankush Varma, Brinda Ganesh, Mainak Sen, Suchismit...
In the past decades, parallel I/O systems have been used widely to support scientific and commercial applications. New data centers today employ huge quantities of I/O systems, wh...
Xiaojun Ruan, Adam Manzanares, Kiranmai Bellam, Xi...