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20152026
most citedUnitary Approximate Message Passing for Sparse Bayesian Learning

82 citations · 246 across the 24 of their papers we have counts for

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Showing 2021Show all

3 papers · 1 filter

stat.ML2021★ 1 cited

On Model Selection Consistency of Lasso for High-Dimensional Ising Models

Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima

We theoretically analyze the model selection consistency of least absolute shrinkage and selection operator (Lasso), both with and without post-thresholding, for high-dimensional I…

cs.LG2021

Ising Model Selection Using -Regularized Linear Regression: A Statistical Mechanics Analysis

Xiangming Meng, Tomoyuki Obuchi, Yoshiyuki Kabashima

We theoretically analyze the typical learning performance of -regularized linear regression (-LinR) for Ising model selection using the replica method from statis…

eess.SP2021★ 82 cited

Unitary Approximate Message Passing for Sparse Bayesian Learning

Man Luo, Qinghua Guo, Ming Jin +4

Sparse Bayesian learning (SBL) can be implemented with low complexity based on the approximate message passing (AMP) algorithm. However, it does not work well for a generic measure…