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» Universal Sparse Modeling
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AOR
2010
15 years 19 days 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 7 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
ICML
2004
IEEE
16 years 4 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 3 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 7 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