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» Every Sequence Is Decompressible from a Random One
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CISS
2008
IEEE
15 years 5 months ago
Near optimal lossy source coding and compression-based denoising via Markov chain Monte Carlo
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
Shirin Jalali, Tsachy Weissman
ICASSP
2008
IEEE
15 years 5 months ago
Compressed sensing with sequential observations
Compressed sensing allows perfect recovery of sparse signals (or signals sparse in some basis) using only a small number of measurements. The results in the literature have focuse...
Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Wills...
COLT
2004
Springer
15 years 4 months ago
Convergence of Discrete MDL for Sequential Prediction
We study the properties of the Minimum Description Length principle for sequence prediction, considering a two-part MDL estimator which is chosen from a countable class of models....
Jan Poland, Marcus Hutter
AUTOMATICA
2006
140views more  AUTOMATICA 2006»
14 years 11 months ago
On a stochastic sensor selection algorithm with applications in sensor scheduling and sensor coverage
In this note we consider the following problem. Suppose a set of sensors is jointly trying to estimate a process. One sensor takes a measurement at every time step and the measure...
Vijay Gupta, Timothy H. Chung, Babak Hassibi, Rich...
MA
2011
Springer
246views Communications» more  MA 2011»
14 years 6 months ago
On the Gaussian approximation of vector-valued multiple integrals
: By combining the findings of two recent, seminal papers by Nualart, Peccati and Tudor, we get that the convergence in law of any sequence of vector-valued multiple integrals Fn ...
Salim Noreddine, Ivan Nourdin