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» Universal Sparse Modeling
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155
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AOR
2010
15 years 4 months ago
Sphere Methods for LP
The sphere method for solving linear programs operates with only a subset of constraints in the model in each iteration, and thus has the advantage of handling instances which may...
Katta G. Murty, Mohammad R. Oskoorouchi
ICASSP
2011
IEEE
14 years 10 months ago
An unsupervised algorithm for hybrid/morphological signal decomposition
The main contribution presented here is an adaptive/unsupervised iterative thresholding algorithm for sparse representation of signals which can be modeled as the sum of two compo...
Matthieu Kowalski, Thomas Rodet
209
Voted
ICML
2004
IEEE
16 years 7 months ago
Kernel conditional random fields: representation and clique selection
Kernel conditional random fields (KCRFs) are introduced as a framework for discriminative modeling of graph-structured data. A representer theorem for conditional graphical models...
John D. Lafferty, Xiaojin Zhu, Yan Liu
ISBI
2004
IEEE
16 years 7 months ago
Level Set Methods for Dynamic Tomography
In this paper, we propose a novel variational framework for the reconstruction of dynamic objects from sparse and noisy tomographic data. Using an object-based scene model, we dev...
Yonggang Shi, William Clement Karl
HUMO
2007
Springer
15 years 11 months ago
Articulated Object Registration Using Simulated Physical Force/Moment for 3D Human Motion Tracking
In this paper, we present a 3D registration algorithm based on simulated physical force/moment for articulated human motion tracking. Provided with sparsely reconstructed 3D human ...
Bingbing Ni, Stefan Winkler, Ashraf A. Kassim