This paper describes a method for the "Analysis and Prediction of Performance for Evolving Architectures" (APPEAR). The method aims at performance estimation of adapted ...
Evgeni M. Eskenazi, Alexandre V. Fioukov, Dieter K...
We present a method for the prediction of the performance of a service-oriented architecture during its early stage of development. The system under scrutiny is modelled with the U...
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Although Locality-Sensitive Hashing (LSH) is a promising approach to similarity search in high-dimensional spaces, it has not been considered practical partly because its search q...
Wei Dong, Zhe Wang, William Josephson, Moses Chari...
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the...