The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
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. ...
It appeared recently that the classical random graph model used to represent real-world complex networks does not capture their main properties. Since then, various attempts have ...
We consider the problem of constructing randomness extractors that are locally computable; that is, read only a small number of bits from their input. As recently shown by Lu (thi...
This paper presents a randomized motion planner for kinodynamic asteroidavoidanceproblems, in which a robot must avoid collision with moving obstacles under kinematic, dynamic con...
Robert Kindel, David Hsu, Jean-Claude Latombe, Ste...