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CORR
2011
Springer
210views Education» more  CORR 2011»
13 years 3 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
ICPR
2006
IEEE
14 years 9 months ago
Exploiting High Dimensional Video Features Using Layered Gaussian Mixture Models
Analysis of video data usually requires training classifiers in high dimensional feature spaces. This paper proposes a layered Gaussian mixture model (LGMM) to exploit high dimens...
Datong Chen, Jie Yang
ICML
2009
IEEE
14 years 9 months ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
CORR
2010
Springer
95views Education» more  CORR 2010»
13 years 8 months ago
Statistical Compressive Sensing of Gaussian Mixture Models
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...
Guoshen Yu, Guillermo Sapiro
ASPDAC
2008
ACM
200views Hardware» more  ASPDAC 2008»
13 years 10 months ago
Non-Gaussian statistical timing analysis using second-order polynomial fitting
In the nanometer manufacturing region, process variation causes significant uncertainty for circuit performance verification. Statistical static timing analysis (SSTA) is thus dev...
Lerong Cheng, Jinjun Xiong, Lei He