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» Every Sequence Is Decompressible from a Random One
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CISS
2008
IEEE
16 years 16 days 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
16 years 15 days 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 11 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»
15 years 6 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»
15 years 1 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