We present an algorithm based on convex optimization for constructing kernels for semi-supervised learning. The kernel matrices are derived from the spectral decomposition of grap...
Xiaojin Zhu, Jaz S. Kandola, Zoubin Ghahramani, Jo...
Computer worms -- malicious, self-propagating programs -- represent a significant threat to large networks. One possible defense, containment, seeks to limit a worm's spread ...
Recent years have seen the emergence of dropletbased microfluidic systems for safety-critical biomedical applications. In order to ensure reliability, microsystems incorporating m...
We propose a data-driven approach to automatically generate a scene where tens to hundreds of characters densely interact with each other. During off-line processing, the close in...
Hubert P. H. Shum, Taku Komura, Masashi Shiraishi,...
The circuit tuning problem is best approached by means of gradient-based nonlinear optimization algorithms. For large circuits, gradient computation can be the bottleneck in the o...
Andrew R. Conn, Ruud A. Haring, Chandramouli Viswe...