Linearly-Involved Moreau-Enhanced-Over-Subspace Model: Debiased Sparse Modeling and Stable Outlier-Robust Regression
Author:
Affiliation:
1. Department of Electronics and Electrical Engineering, Keio University, Yokohama, Kanagawa, Japan
2. Department of Information and Communications Engineering, Tokyo Institute of Technology, Meguro-ku, Tokyo, Japan
Funder
JSPS
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Signal Processing
Link
http://xplorestaging.ieee.org/ielx7/78/10040758/10089559.pdf?arnumber=10089559
Reference70 articles.
1. $\ell _{p}$ -Regularized Least Squares $(0<p<1)$ and Critical Path
2. Distributed Sparse Optimization With Weakly Convex Regularizer: Consensus Promoting and Approximate Moreau Enhanced Penalties Towards Global Optimality
3. Exact Reconstruction of Sparse Signals via Nonconvex Minimization
4. Learning Sparse Graph with Minimax Concave Penalty under Gaussian Markov Random Fields
5. Some sharp performance bounds for least squares regression with L1 regularization
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2. Distributed Stable Outlier-Robust Signal Recovery using Minimax Concave Loss;2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP);2023-09-17
3. Dispersed-Sparsity-Aware Lms Algorithm for Scattering-Sparse System Identification;2023
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