Efficient Algorithms for L0 Regularized Learning
machine-learning compressed-sensing feature-selection regularization sparse-regression sparse-modeling l0learn l0-regularization
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Updated
Jan 22, 2024 - C++
Efficient Algorithms for L0 Regularized Learning
Detecting Beneficial Feature Interactions for Recommender Systems, AAAI 2021
Learn how to use L0 regularization
The L0-SIGN implementation.
An Exact L0-penalized Problem Solver.
A header-only C++ library for solving Sparse Modeling Problems via Biconjugate Convex Relaxation Techniques.
A hands-on guide to model selection, emphasizing high-dimensional problems, Bayesian model selection and averaging, and L0 criteria
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