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Multi-attribute graph learning for geoscience applications

delete2025-10-15
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PRE
AI
S
Sanath S Soni *
P
Prabhu Babu
DOI：10.1016/j.sigpro.2025.110335delete
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Abstract

Abstract

En 中文
• A BCD-based approach with ℓ0-norm penalty to estimate a sparse precision matrix for multi-attribute graph learning. • Overcoming biases introduced by traditional ℓ1-norm penalty via usage of ℓ0-norm penalty. • Employment of the Extended Bayesian Information Criterion (EBIC) for the hyperparameter tuning. • Computationally efficient procedure for selection of penalty parameter.

Journal

Signal Processing cover
Signal Processing
IF:
3.6
Papers:
9.9K
Citations:
1.7W

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No organization information available