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Found 5 papers, 1 papers with code
0/1 Deep Neural Networks via Block Coordinate Descent
The step function is one of the simplest and most natural activation functions for deep neural networks (DNNs).
Ranked #1 on
Dichotomous Image Segmentation
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Support Vector Machine Classifier via $L_{0/1}$ Soft-Margin Loss
To distinguish all of them, in this paper, we introduce a new model equipped with an $L_{0/1}$ soft-margin loss (dubbed as $L_{0/1}$-SVM) which well captures the nature of the binary classification.
Single and Union Non-parallel Support Vector Machine Frameworks
The other type constructs all the hyperplanes simultaneously, and it solves one big optimization problem with the ascertained loss of each sample.
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
Sparse and Low-Rank Covariance Matrices Estimation
This paper aims at achieving a simultaneously sparse and low-rank estimator from the semidefinite population covariance matrices.
