Polynomial chaos theory (PCT) has been proven to be an efficient and effective way to represent and propagate uncertainty through system models and algorithms in general. In partic...
re a popular form of abstract computation. Being more general than monads, they are more broadly applicable, and in parare a good abstraction for signal processing and dataflow co...
The Value Sensitive Design (VSD) methodology provides a comprehensive framework for advancing a value-centered research and design agenda. Although VSD provides helpful ways of th...
Christopher A. Le Dantec, Erika Shehan Poole, Susa...
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
The theory of compressed sensing shows that samples in the form of random projections are optimal for recovering sparse signals in high-dimensional spaces (i.e., finding needles ...
Rui M. Castro, Jarvis Haupt, Robert Nowak, Gil M. ...