Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Decoupling capacitance (decap) is an efficient way to reduce transient noise in on-chip power supply networks. However, excessive decap may cause more leakage power, chip resource...
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
In this paper, we address a challenging image segmentation problem called multiple foreground cosegmentation (MFC), which concerns a realistic scenario in general Webuser photo se...
To make efficient use of CMPs with tens to hundreds of cores, it is often necessary to exploit fine-grain parallelism. However, managing tasks of a few thousand instructions is ...
Daniel Sanchez, Richard M. Yoo, Christos Kozyrakis