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95
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ICASSP
2009
IEEE
15 years 4 months ago
Compressive spectral estimation for nonstationary random processes
We propose a “compressive” estimator of the Wigner-Ville spectrum (WVS) for time-frequency sparse, underspread, nonstationary random processes. A novel WVS estimator involving...
Alexander Jung, Georg Tauböck, Franz Hlawatsc...
97
Voted
JMLR
2010
157views more  JMLR 2010»
14 years 4 months ago
Why are DBNs sparse?
Real stochastic processes operating in continuous time can be modeled by sets of stochastic differential equations. On the other hand, several popular model families, including hi...
Shaunak Chatterjee, Stuart Russell
178
Voted
ICDT
2009
ACM
148views Database» more  ICDT 2009»
15 years 10 months ago
Tight results for clustering and summarizing data streams
In this paper we investigate algorithms and lower bounds for summarization problems over a single pass data stream. In particular we focus on histogram construction and K-center c...
Sudipto Guha
CORR
2011
Springer
210views Education» more  CORR 2011»
14 years 4 months ago
Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Guoshen Yu, Guillermo Sapiro
MOC
2010
14 years 4 months ago
Sharply local pointwise a posteriori error estimates for parabolic problems
Abstract. We prove pointwise a posteriori error estimates for semi- and fullydiscrete finite element methods for approximating the solution u to a parabolic model problem. Our esti...
Alan Demlow, Charalambos Makridakis