Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
Abstract. Monolithic finite-state probabilistic programs have been abstractly modeled by finite Markov chains, and the algorithmic verification problems for them have been inves...
We introduce cube summing, a technique that permits dynamic programming algorithms for summing over structures (like the forward and inside algorithms) to be extended with non-loc...
In this paper we present an efficient algorithm for extracting the complete statistical distribution of the input impedance of interconnect structures in the presence of a large n...
The paper introduces a family of scheduling problems called fault-tolerant programs scheduling FTPS. Since FTPS problems are, in general, computationally di cult, a challenge is to...
Piotr Jedrzejowicz, Ireneusz Czarnowski, Henryk Sz...