—We propose a steepest descent method to compute optimal control parameters for balancing between multiple performance objectives in stateless stochastic scheduling, wherein the ...
Chris Y. T. Ma, David K. Y. Yau, Nung Kwan Yip, Na...
We present a framework for clustering distributed data in unsupervised and semi-supervised scenarios, taking into account privacy requirements and communication costs. Rather than...
In this paper, we combine two approaches to handling uncertainty: we use techniques for finding optimal solutions in the expected sense to solve combinatorial optimization proble...
Michael Benisch, Amy R. Greenwald, Victor Narodits...
Abstract. We study the problem of applying statistical methods for approximate model checking of probabilistic systems against properties encoded as PCTL formulas. Such approximate...
— In this paper we present analytical techniques that can be used to better understand the behavior of malware, a generic term that refers to all kinds of malicious software prog...