A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
Distributed storage systems often use data replication to mask failures and guarantee high data availability. Node failures can be transient or permanent. While the system must ge...
Jing Tian, Zhi Yang, Wei Chen, Ben Y. Zhao, Yafei ...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
istic Abstract Interpretation of Imperative Programs using Truncated Normal Distributions Michael J. A. Smith1 ,2 Laboratory for Foundations of Computer Science University of Edinb...
—Most analysis methods for real-time systems assume that all the components of the system are at roughly the same stage of development and can be expressed in a single notation, ...
George S. Avrunin, James C. Corbett, Laura K. Dill...