Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
We propose a new algorithm for learning kernels for variants of the Normalized Cuts (NCuts) objective – i.e., given a set of training examples with known partitions, how should ...
The Internet has become a complex system with increasing numbers of end-systems, applications, protocols and types of networks. Although we have a good understanding of how data i...
Tacio Santos, Christian Henke, Carsten Schmoll, Ta...
This paper presents a framework, integrated into the X3D file format, for the streaming of 3D content in the context of remote scientific visualization; a progressive mesh compres...
In using image analysis to assist a driver to avoid obstacles on the road, traditional approaches rely on various detectors designed to detect different types of objects. We propo...
Qi Wu, Wende Zhang, Tsuhan Chen, B. V. K. Vijaya K...