Cardinality-constrained structured data-fitting problems
From MaRDI portal
Publication:6584338
DOI10.5802/ojmo.27MaRDI QIDQ6584338
Michael P. Friedlander, Zhenan Fan, Huang Fang
Publication date: 6 August 2024
Published in: OJMO. Open Journal of Mathematical Optimization (Search for Journal in Brave)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Explicit Sensor Network Localization using Semidefinite Representations and Facial Reductions
- A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
- Convex multi-task feature learning
- Level-set methods for convex optimization
- The convex geometry of linear inverse problems
- ``Active-set complexity of proximal gradient: how long does it take to find the sparsity pattern?
- High-dimensional graphs and variable selection with the Lasso
- Convex Recovery of a Structured Signal from Independent Random Linear Measurements
- Low-Rank Spectral Optimization via Gauge Duality
- PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming
- Identifying Active Manifolds in Regularization Problems
- Julia: A Fresh Approach to Numerical Computing
- Robust principal component analysis?
- Sparse Optimization with Least-Squares Constraints
- Exact Regularization of Convex Programs
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Probing the Pareto Frontier for Basis Pursuit Solutions
- On the Identification of Active Constraints
- Atomic Decomposition by Basis Pursuit
- A Spectral Bundle Method for Semidefinite Programming
- Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso
- Gap Safe screening rules for sparsity enforcing penalties
- Safe Feature Elimination in Sparse Supervised Learning
- An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity
- Foundations of Gauge and Perspective Duality
- Model Selection and Estimation in Regression with Grouped Variables
- For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution
- Convex Analysis
- Phase Retrieval via Matrix Completion
- Compressed sensing
- A second-order bundle method to minimize the maximum eigenvalue function.
- Polar deconvolution of mixed signals
This page was built for publication: Cardinality-constrained structured data-fitting problems