We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
Simultaneous Multithreading machines fetch and execute instructions from multiple instruction streams to increase system utilization and speedup the execution of jobs. When there ...
In this paper, an approach based on the combination of discrete Hidden Markov Models (HMMs) in the ROC space is proposed to improve the performance of off-line signature verificat...
This paper demonstrates how to reduce the hand labeling effort considerably by 3D information in an object detection task. In particular, we demonstrate how an efficient car detec...
Stefan Kluckner, Georg Pacher, Helmut Grabner, Hor...
We propose in this paper a heuristic for mapping a set of interacting tasks of a parallel application onto a heterogeneous computing platform such as a computational grid. Our nov...