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Structured Sparsity: Theory, Algorithms and Applications
.Introduction
This work investigates
a new learning formulation called structured sparsity, which is a
natural extension of the standard sparsity concept in
statistical learning and compressive sensing. By allowing arbitrary
structures on the feature set, this concept generalizes the group
sparsity idea. A general theory is developed for learning with structured
sparsity, based on the notion of coding complexity associated with
the structure. Moreover, efficient algorithms are developed to solve
the structured sparsity problems. It is general enough to be applied
in differnt applications to achieve bette performance.
.Theory
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Junzhou Huang, Tong Zhang,
Dimitris Metaxas, "Learning with Structured Sparsity",
The 26th International Conference on Machine Learning, ICML’09,
Montreal, Quebec, Canada, June, 2009. [PDF]
[SLIDES] [CODE]
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Junzhou Huang and Tong Zhang.
"The Benefit of Group Sparsity", Annals of Statistics,
Volume 38, Number 4, pp.1978-2004, August 2010. [PDF]
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Junzhou Huang, Tong Zhang
and Dimitris Metaxas."Learning with Structured Sparsity",
Journal of Machine Learning Research, Volume 12, pp. 3371-3412,
November 2011 (Tech Report arXiv:0903.3002, March 2009).
[PDF] [CODE]
Algorithms and Applications on Medical Imaging
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Zheng Xu, Sheng Wang, Yeqing Li, Feiyun Zhu
and Junzhou Huang, "PRIM: An Efficient Preconditioning
Iterative Reweighted Least Squares Method for Parallel Brain MRI
Reconstruction", Neuroinformatics, Volume 16, Issue
3-4, pp. 425-430, October 2018. [CODE]
- Chen Chen, Lei He, Hongsheng Li and Junzhou Huang,
"Fast Iteratively Reweighted Least Squares Algorithms for Analysis-Based
Sparse Reconstruction", Medical Image Analysis, Volume
49, pp.141-152, October 2018. [CODE]
- Jiawen Yao, Zheng Xu, Xiaolei Huang and Junzhou Huang,
“An Efficient Algorithm for Dynamic MRI Using Low-rank and Total
Variation Regularization”, Medical Image Analysis,
Volume 44, pp. 14-27, February 2018. [CODE]
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Zheng Xu, Yeqing Li, Leon Axel, Junzhou
Huang, "Efficient Preconditioning in Joint Total
Variation Regularized Parallel MRI Reconstruction", In Proc.
of the 18th Annual International Conference on Medical Image Computing
and Computer Assisted Intervention, MICCAI'15, Munich, Germany,
October 2015. [CODE]
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Ruoyu Li, Yeqing Li, Ruogu Fang, Shaoting Zhang,
Hao Pan, Junzhou Huang, "Fast Preconditioning
for Accelerated Multi-Contrast MRI Reconstruction", In Proc.
of the 18th Annual International Conference on Medical Image Computing
and Computer Assisted Intervention, MICCAI'15, Munich, Germany,
October 2015. (Oral Presentation)
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Jiawen Yao, Zheng Xu, Xiaolei Huang, Junzhou
Huang, "Accelerated Dynamic MRI Reconstruction with
Total Variation and Nuclear Norm Regularization", In Proc.
of the 18th Annual International Conference on Medical Image Computing
and Computer Assisted Intervention, MICCAI'15, Munich, Germany,
October 2015. [CODE]
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Junzhou Huang, Chen Chen,
Leon Axel, "Fast Multi-contrast MRI Reconstruction",
Magnetic Resonance Imaging, Volume 32, Issue 10, pp. 1344–1352,
December 2014. [CODE]
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Chen Chen and Junzhou Huang,
”Exploiting the wavelet structure in Compressed Sensing
MRI”, Magnetic Resonance Imaging, Volume 32,Issue 10, pp.
1377–1389, December 2014. [CODE]
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Chen Chen, Yeqing Li, Leon Axel and Junzhou
Huang, “Real Time Dynamic MRI with Dynamic Total
Variation”, In Proc. of the 16th Annual International Conference
on Medical Image Computing and Computer Assisted Intervention,
MICCAI'14, Boston, USA, September 2014. [CODE]
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Chen Chen and Junzhou Huang,
"The Benefit of Tree Sparsity in Accelerated MRI", Medical
Image Analysis, Volume 18, Issue 6, pp. 834–842, August
2014. [CODE]
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Chen Chen, Yeqing Li, and Junzhou Huang,
"Forest Sparsity for Multi-channel Compressive Sensing",
IEEE Transactions on Signal Processing, Volume 62, Issue 11, pp.
2803-2813, June 2014. [CODE]
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Chen Chen, Yeqing Li and Junzhou Huang,
"Calibrationless Parallel MRI with Joint Total Variation
Regularization", In Proc. of the 16th Annual International
Conf. on Medical Image Computing and Computer Assisted Intervention
(MICCAI), 2013. [CODE]
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Chen Chen and Junzhou Huang,
"Compressive Sensing MRI with Wavelet Tree Sparsity",
In Proc. of the 26th Annual Conference on Neural Information Processing
Systems (NIPS), Nevada, USA, December 2012. [PDF]
[CODE]
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Chen Chen, Junzhou Huang
and Leon Axel, "Accelerated Parallel Magnetic Resonance Imaging
with Joint Gradient and Wavelet Sparsity'', MICCAI Workshop on
Sparsity Techniques in Medical Imaging, Nice, France, October
2012. [PDF]
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Chen Chen and Junzhou Huang,
"The Benefit of Tree Sparsity in Accelerated MRI", MICCAI
Workshop on Sparsity Techniques in Medical Imaging, Nice, France,
October 2012. [PDF] ( Best
Paper Award)
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Junzhou Huang, Fei Yang, "Compressed
Magnetic Resonace Imaging Based on Wavelet Sparsity and Nonlocal
Total Variation". IEEE International Symposium on Biomedical
Imaging, ISBI'12, Bacelona, Spain, May 2012. [PDF]
[CODE]
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Junzhou Huang, Shaoting Zhang
and Dimitris Metaxas, "Efficient MR Image Reconstruction
for Compressed MR Imaging ", In Proc. of the 13th Annual
International Conf. on Medical Image Computing and Computer Assisted
Intervention, MICCAI’2010, Beijing, China, September 2010..
[PDF] [SLIDES]
[CODE] [ Supplemental]
( MICCAI Young Scientist Award)
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Junzhou Huang, Zhen Qian,
Xiaolei Huang, Dimitris
Metaxas, Leon Axel, "Tag
Separation in Cardiac Tagged MRI", In Proc. of the
11th Annual International Conference on Medical Image Computing
and Computer Assisted Intervention, MICCAI'08, New York,
USA, September 2008. [ PROJECT]
Algorithms and Applications on Computer
Vision
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Baiyang Liu, Lin Yang, Junzhou Huang,
Peter Meer, Leiguang Gong, Casimir Kulikowski, " Robust
and Fast Collaborative Tracking with Two Stage Sparse Optimization",
In Proc. of the 11th European Conference
on Computer Vision, ECCV'10, Crete, Greece, September 2010.
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Shaoting Zhang, Junzhou
Huang,Yuchi
Huang, Yang Yu, Hongsheng Li, Dimitris
Metaxas, "Automatic
Image Annotation Using Group Sparsity", In Proc.
of the IEEE Computer Society Conference on Computer Vision and
Pattern Recognition, CVPR'10, San Francisco, USA, June 2010.
Oral presentation. [CODE]
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Baiyang Liu, Junzhou Huang, Casimir Kulikowski, Lin
Yang, "Robust
Tracking Using Local Sparse Appearance Model and K-Selection",
In Proc. of the IEEE Computer Society Conference on Computer
Vision and Pattern Recognition, CVPR'11, Colorado Springs,
Colorado, USA, June 2011. Oral presentation.
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Shaoting Zhang, Yiqiang Zhan, Maneesh Dewan, Junzhou Huang,
Dimitris Metaxas and Xiang Zhou, "Sparse
Shape Composition: A New Framework for Shape Prior Modeling",
In Proc. of the IEEE Computer Society Conference on Computer
Vision and Pattern Recognition, CVPR'11, Colorado Springs,
Colorado, USA, June 2011.
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Lin Zhong, Qingshan Liu, Peng Yang, Bo Liu,
Junzhou Huang and Dimitris Metaxas, " Learning
Active Facial Patches for Expression Analysis". In
Proc. of the IEEE Computer Society Conference on Computer Vision
and Pattern Recognition, CVPR'12, Providence, Rhode Island,
USA, June 2012.
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Shaoting Zhang, Yiqiang Zhan, Xinyi Cui, Mingchen
Gao, Junzhou Huang, Dimitris Metaxas, " 3D
Anatomical Shape Atlas Construction using Mesh Quality Preserved
Deformable Models", Computer Vision and Image Understanding,
Volume 117, Issue 9, pp. 1061-1071, September 2013.
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Chen Chen, Junzhou Huang,
Lei He, and Hongsheng Li, " Preconditioning
for Accelerated Iteratively Reweighted Least Squares in Structured
Sparsity Reconstruction", In Proc. of IEEE
Conference on Computer Vision and Pattern Recognition, CVPR'14,
Columbus, Ohio, USA, June 2014. (Oral Presentation) [CODE]
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Chen Chen, Yeqing Li, Wei Liu, and Junzhou
Huang, " Image
Fusion with Local Spectral Consistency and Dynamic Gradient Sparsity",
In Proc. of IEEE Conference on Computer Vision and Pattern
Recognition, CVPR'14, Columbus, Ohio, USA, June 2014. (Oral
Presentation) [CODE]
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