In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Large intersubject variability is a well-described feature of fMRI studies, making inter-group inference, of critical importance for biological interpretation, difficult. Therefor...
Martin J. McKeown, Junning Li, Xuemei Huang, Z. Ja...
The paper presents approaches to the validation of optimizing compilers. The emphasis is on aggressive and architecture-targeted optimizations which try to obtain the highest perf...
Lenore D. Zuck, Amir Pnueli, Yi Fang, Benjamin Gol...
Although reactive and graphically rich interfaces are now mainstream, their development is still a notoriously difficult task. This paper presents Hayaku, a toolset that supports...
Recently web-based educational systems collect vast amounts of data on user patterns, and data mining methods can be applied to these databases to discover interesting associations...
Behrouz Minaei-Bidgoli, Gerd Kortemeyer, William F...