Search Results for author:
Found 2 papers, 1 papers with code
Global and Quadratic Convergence of Newton Hard-Thresholding Pursuit
Algorithms based on the hard thresholding principle have been well studied with sounding theoretical guarantees in the compressed sensing and more general sparsity-constrained optimization.
Optimization and Control
Convex Optimization Learning of Faithful Euclidean Distance Representations in Nonlinear Dimensionality Reduction
The other is that they are slow in computation when the data points are beyond moderate size.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
