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Found 3 papers, 1 papers with code
Fréchet regression for multi-label feature selection with implicit regularization
Fr\'echet regression extends linear regression to model complex responses in metric spaces, making it particularly relevant for multi-label regression, where each instance can have multiple associated labels.
A Two-Fold Patch Selection Approach for Improved 360-Degree Image Quality Assessment
This article presents a novel approach to improving the accuracy of 360-degree perceptual image quality assessment (IQA) through a two-fold patch selection process.
Implicit Regularization for Multi-label Feature Selection
In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit regularization and label embedding.
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