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MMAS
2010
Springer
13 years 3 months ago
A Nonlinear PDE-Based Method for Sparse Deconvolution
In this paper, we introduce a new nonlinear evolution partial differential equation for sparse deconvolution problems. The proposed PDE has the form of continuity equation that ar...
Yu Mao, Bin Dong, Stanley Osher
PAMI
2012
11 years 11 months ago
Face Recognition Using Sparse Approximated Nearest Points between Image Sets
—We propose an efficient and robust solution for image set classification. A joint representation of an image set is proposed which includes the image samples of the set and thei...
Yiqun Hu, Ajmal S. Mian, Robyn A. Owens
TSP
2011
151views more  TSP 2011»
13 years 3 months ago
Stochastic Models for Sparse and Piecewise-Smooth Signals
Abstract—We introduce an extended family of continuous-domain stochastic models for sparse, piecewise-smooth signals. These are specified as solutions of stochastic differential...
Michael Unser, Pouya Dehghani Tafti
JMLR
2010
157views more  JMLR 2010»
13 years 3 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
ICASSP
2011
IEEE
13 years 7 days ago
Revisiting adaptive least-squares estimation and application to online sparse signal recovery
This paper presents a novel time-adaptive estimation technique by revisiting the classical Wiener-Hopf equation. Any convex and not necessarily differentiable function can be used...
Konstantinos Slavakis, Yannis Kopsinis, Sergios Th...