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Found 9 papers, 1 papers with code
A Block Coordinate Descent Method for Nonsmooth Composite Optimization under Orthogonality Constraints
We propose a breakpoint searching method and a fifth-order iterative method to solve this problem efficiently and effectively.
Coordinate Descent Methods for Fractional Minimization
This problem is difficult to solve since it is non-convex.
Coordinate Descent Methods for DC Minimization: Optimality Conditions and Global Convergence
This paper proposes a coordinate descent method for minimizing a class of DC functions based on sequential nonconvex approximation.
A Decomposition Algorithm for the Sparse Generalized Eigenvalue Problem
The sparse generalized eigenvalue problem arises in a number of standard and modern statistical learning models, including sparse principal component analysis, sparse Fisher discriminant analysis, and sparse canonical correlation analysis.
Numerical Analysis
A Coordinate-wise Optimization Algorithm for Sparse Inverse Covariance Selection
Sparse inverse covariance selection is a fundamental problem for analyzing dependencies in high dimensional data.
GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization
In addition, we develop a new technique to establish the global convergence of the GSOS algorithm.
A Matrix Splitting Method for Composite Function Minimization
Incorporating a new Gaussian elimination procedure, the matrix splitting method achieves state-of-the-art performance.
Convex Optimization for Linear Query Processing under Approximate Differential Privacy
This paper points out that under ($\epsilon$, $\delta$)-differential privacy, the optimal solution of the above constrained optimization problem in search of a suitable strategy can be found, rather surprisingly, by solving a simple and elegant convex optimization program.
L0TV: A New Method for Image Restoration in the Presence of Impulse Noise
This paper focuses on TV for image restoration in the presence of impulse noise.
