In our paper titled "Algebraic Signal Processing Theory: Foundation and 1-D Time" appearing in this issue of the IEEE TRANSACTIONS ON SIGNAL PROCESSING, we presented the ...
We demonstrate a method for describing data-flow analyses based program optimizations as compositional type systems with a transformation component. Analysis results are presented...
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
— In this paper, we present the first multi-objective microarchitectural floorplanning algorithm for designing highperformance, high-reliability processors in the early design ...
Michael B. Healy, Mario Vittes, Mongkol Ekpanyapon...
Labelled Markov processes (LMPs) are automata whose transitions are given by probability distributions. In this paper we present a ‘universal’ LMP as the spectrum of a commutat...