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Journal of Machine Learning Research, ISSN 1532-4435, 06/2011, Volume 12, pp. 1865 - 1892
Journal Article
Signal Processing, ISSN 0165-1684, 10/2018, Volume 151, pp. 119 - 129
•L1 minimization method using recursive reduction of dimensionality is proposed.•It can be used for robust regression, system identification and LAD... 
L1 norm | Linear big data problem | Least absolute deviation | Weighted median | Reduction of dimensionality | SYSTEM | ALGORITHM | ERROR | L | ABSOLUTE VALUE REGRESSION | DEVIATIONS | ENGINEERING, ELECTRICAL & ELECTRONIC | Electrical engineering | Usage | Big data | Algorithms | Analysis
Journal Article
Signal Processing, ISSN 0165-1684, 03/2015, Volume 108, pp. 459 - 475
Compressed sensing using ℓ1 minimization has been widely and successfully applied. To further enhance the sparsity, a non-convex and piecewise linear penalty... 
ℓ1 minimization | Thresholding algorithm | Compressed sensing | Non-convex penalty | minimization
Journal Article
Computer Communications, ISSN 0140-3664, 09/2018, Volume 127, pp. 122 - 130
•A compressed sensing based loss tomography scheme is proposed.•The scheme uses weighted L1 minimization to infer link loss rate.•The weights are used to... 
Network tomography | Compressed sensing | Weighted ℓ1 minimization | Congestion localization | minimization | Weighted ℓ
Journal Article
International Journal for Numerical Methods in Fluids, ISSN 0271-2091, 08/2018, Volume 87, Issue 12, pp. 628 - 651
Summary We are interested in the model reduction techniques for hyperbolic problems, particularly in fluids. This paper, which is a continuation of an earlier... 
reduced‐order models | nonlinear hyperbolic problems | L1 minimization | minimization | reduced-order models | Fluids | Compressibility | Methodology | Computational fluid dynamics | Mathematical models | Model reduction | Optimization
Journal Article
Mathematical Programming, ISSN 0025-5610, 2013, Volume 147, Issue 1-2, pp. 277 - 307
Journal Article
Journal of Visual Communication and Image Representation, ISSN 1047-3203, 06/2015, Volume 31, pp. 112 - 124
Compressed Sensing theory has been found with successful reconstructions of MR images from incomplete measurements by prompting sparsity in MR images. Research... 
Motion estimation | Augmented Lagrangian multiplier | Convex optimization | Alternating direction minimization | Compressed Sensing | Reference-driven MRI reconstruction | l1 minimization | Motion compensation | Cardiac MRI | Magnetic resonance imaging | Methods
Journal Article
Proceedings of SPIE - The International Society for Optical Engineering, ISSN 0277-786X, 2017, Volume 10211
Conference Proceeding
European Journal of Operational Research, ISSN 0377-2217, 03/2019, Volume 273, Issue 2, pp. 754 - 771
•Traditional mean-variance strategy is worse than monkey picking in high dimensions.•A linear-programming-based estimator/remedy for mean-variance strategy is... 
Investment analysis | Dynamic mean-variance portfolio | ℓ1 minimization | High-dimensional portfolio selection | Sparse portfolio | minimization | COVARIANCE-MATRIX | OPERATIONS RESEARCH & MANAGEMENT SCIENCE | DANTZIG SELECTOR | MARKOWITZ | CONVERGENCE | OPTIMIZATION | l minimization | Minimization (Electronics) | Management science | Management | Analysis
Journal Article
IEICE Transactions on Communications, ISSN 0916-8516, 11/2015, Volume E98B, Issue 11, pp. 2307 - 2313
Journal Article
IEEE Transactions on Information Theory, ISSN 0018-9448, 01/2015, Volume 61, Issue 1, pp. 469 - 478
Journal Article
JOURNAL OF MACHINE LEARNING RESEARCH, ISSN 1532-4435, 06/2011, Volume 12, pp. 1865 - 1892
We describe and analyze two stochastic methods for l(1) regularized loss minimization problems, such as the Lasso. The first method updates the weight of a... 
REGRESSION | GRADIENT DESCENT | optimization | L1 regularization | coordinate descent | CONVERGENCE | sparsity | mirror descent | COORDINATE | AUTOMATION & CONTROL SYSTEMS | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Signal Processing, ISSN 0165-1684, 2012, Volume 92, Issue 4, pp. 905 - 911
Sparse FIR filters have lower implementation complexity than full filters, while keeping a good performance level. This paper describes a new method for... 
Reweighted l1 minimization | Greedy algorithms | Sparse filters | Reweighted l | minimization
Journal Article
EURASIP Journal on Advances in Signal Processing, ISSN 1687-6172, 12/2018, Volume 2018, Issue 1, pp. 1 - 26
Journal Article
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