scientific article; zbMATH DE number 6982922
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Publication:4558490
zbMath1471.90114MaRDI QIDQ4558490
Tong Zhang, Ping Li, Xiaotong Yuan
Publication date: 22 November 2018
Full work available at URL: http://jmlr.csail.mit.edu/papers/v18/14-415.html
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Sparse inverse covariance estimation with the graphical lasso
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Iterative hard thresholding for compressed sensing
- Fast global convergence of gradient methods for high-dimensional statistical recovery
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
- Introductory lectures on convex optimization. A basic course.
- On the conditions used to prove oracle results for the Lasso
- High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
- Alternating direction method for covariance selection models
- Sparsity Constrained Nonlinear Optimization: Optimality Conditions and Algorithms
- Sparse Recovery Algorithms: Sufficient Conditions in Terms of Restricted Isometry Constants
- Compressed Sensing With Nonlinear Observations and Related Nonlinear Optimization Problems
- Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints
- A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
- Hard Thresholding Pursuit: An Algorithm for Compressive Sensing
- Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
- Graphical Models, Exponential Families, and Variational Inference
- Smooth Optimization Approach for Sparse Covariance Selection
- Introduction to Graphical Modelling
- Linear Convergence of Stochastic Iterative Greedy Algorithms With Sparse Constraints
- Sparse Approximate Solutions to Linear Systems
- Matching pursuits with time-frequency dictionaries
- Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
- Greedy Sparsity-Constrained Optimization
- Stable signal recovery from incomplete and inaccurate measurements
- Compressed sensing