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Sparse regression using mixed norms
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Cited by
Block-Sparse Signals: Uncertainty Relations and Efficient Recovery
Eldar, Y. C., Kuppinger, P., & Bolcskei, H. (2010) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2010.2044837 · Cited by 1,313
Visual Classification With Multitask Joint Sparse Representation
Yuan, X.-T., Liu, X., & Yan, S. (2012) · IEEE Transactions on Image Processing · doi:10.1109/tip.2012.2205006 · Cited by 364
Sparse methods for direction-of-arrival estimation
Yang, Z., Li, J., Stoica, P., & Xie, L. (2018) · Academic Press Library in Signal Processing, Volume 7 · doi:10.1016/b978-0-12-811887-0.00011-0 · Cited by 332
Similarity Learning with Spatial Constraints for Person Re-identification
Chen, D., Yuan, Z., Chen, B., & Zheng, N. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.142 · Cited by 320
Hyperspectral Image Unmixing With Endmember Bundles and Group Sparsity Inducing Mixed Norms
Drumetz, L., Meyer, T. R., Chanussot, J., Bertozzi, A. L., & Jutten, C. (2019) · IEEE Transactions on Image Processing · doi:10.1109/tip.2019.2897254 · Cited by 104
Metadata
- Authors
- Kowalski, M.
- Venue
- Applied and Computational Harmonic Analysis
- Publisher
- Elsevier BV
- Published
- 2009-11
- Volume
- 27
- Issue
- 3
- Pages
- 303-324
- ISSN
- 1063-5203 (ISSN-L)
- OpenAlex
- W2054110507
- Cited by
- 265
- References
- 0
- FWCI
- 14.50
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Kowalski, M. (2009). Sparse regression using mixed norms. Applied and Computational Harmonic Analysis. https://doi.org/10.1016/j.acha.2009.05.006
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.