Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
Applications such as traffic engineering and network provisioning can greatly benefit from knowing, in real time, what is the largest input rate at which it is possible to transmit...
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such...
A detailed step-by-step approach is presented to optimize, standardize, and automate the process of unmanned vehicle controller design, evaluation, validation and verification, fol...
Daniel Ernst, Kimon P. Valavanis, Richard Garcia, ...
Abstract--Reliability and sensitivity analysis is a key component in the design, tuning, and maintenance of network systems. Tremendous research efforts have been expended in this ...