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...
Constraint-based random simulation is state-of-the-art in verification of multi-million gate industrial designs. This method is based on stimulus generation by constraint solving...
— This paper argues for the need to address the issue of multi-channel network performance under constraints on channel switching. We present examples from emergent directions in...
Problems that can be sampled randomly are a good source of test suites for comparing quality of constraint satisfaction techniques. Quasigroup problems are representatives of struc...