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eess.SP2021
Asymptotics of Proximity Operator for Squared Loss and Performance Prediction of Nonconvex Sparse Signal Recovery
Ryo Hayakawa
Proximal splitting-based convex optimization is a promising approach to linear inverse problems because we can use some prior knowledge of the unknown variables explicitly. An unde…
eess.SP2020★ 4 cited
Noise Variance Estimation Using Asymptotic Residual in Compressed Sensing
Ryo Hayakawa
In compressed sensing, measurements are typically contaminated by additive noise, and therefore, information about the noise variance is often needed to design algorithms. In this…
eess.SP2020★ 1 cited
Asymptotic Performance Prediction for ADMM-Based Compressed Sensing
Ryo Hayakawa
In this paper, we propose a method to predict the asymptotic performance of the alternating direction method of multipliers (ADMM) for compressed sensing, where we reconstruct an u…