Abstract. We study computationally hard combinatorial problems arising from the important engineering question of how to maximize the number of connections that can be simultaneous...
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
In this paper, we propose a new stereo matching method using the population-based Markov Chain Monte Carlo (Pop-MCMC), which belongs to the sampling-based methods. Since the previo...
Wonsik Kim (Seoul National University), Joonyoung ...
For statistical timing and power analysis that are very important problems in the sub-100nm technologies, stochastic analysis of power grids that characterizes the voltage fluctua...
Praveen Ghanta, Sarma B. K. Vrudhula, Sarvesh Bhar...
Background: Stochastic simulation has become a useful tool to both study natural biological systems and design new synthetic ones. By capturing the intrinsic molecular fluctuation...
Howard Salis, Vassilios Sotiropoulos, Yiannis N. K...