Learning the underlying model from distributed data is often useful for many distributed systems. In this paper, we study the problem of learning a non-parametric model from distr...
This paper advocates a novel approach to the construction of secure software: controlling information flow and maintaining integrity via monadic encapsulation of effects. This ap...
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...
— Recent progress in High-Level Synthesis (HLS) es has helped raise the abstraction level of FPGA programming. However implementation and performance evaluation of the HLS-genera...
Alexandros Papakonstantinou, Yun Liang, John A. St...
To improve its process modeling capabilities, Los Alamos has worked toward integrating dose modeling tools with advanced discrete-event simulation tools. To date, dose information...
George Tompkins, Drew E. Kornreich, Robert Y. Park...