A unifying tutorial on approximate message passing
Over the last decade or so, Approximate Message Passing (AMP) algorithms have become
extremely popular in various structured high-dimensional statistical problems. Although the …
extremely popular in various structured high-dimensional statistical problems. Although the …
Bayes-optimal convolutional AMP
K Takeuchi - IEEE Transactions on Information Theory, 2021 - ieeexplore.ieee.org
This paper proposes Bayes-optimal convolutional approximate message-passing (CAMP)
for signal recovery in compressed sensing. CAMP uses the same low-complexity matched …
for signal recovery in compressed sensing. CAMP uses the same low-complexity matched …
On the convergence of orthogonal/vector AMP: Long-memory message-passing strategy
K Takeuchi - IEEE Transactions on Information Theory, 2022 - ieeexplore.ieee.org
Orthogonal/vector approximate message-passing (AMP) is a powerful message-passing
(MP) algorithm for signal reconstruction in compressed sensing. This paper proves the …
(MP) algorithm for signal reconstruction in compressed sensing. This paper proves the …
A non-asymptotic analysis of generalized approximate message passing algorithms with right rotationally invariant designs
C Cademartori, C Rush - arXiv preprint arXiv:2302.00088, 2023 - arxiv.org
Approximate Message Passing (AMP) algorithms are a class of iterative procedures for
computationally-efficient estimation in high-dimensional inference and estimation tasks. Due …
computationally-efficient estimation in high-dimensional inference and estimation tasks. Due …
Displacement prediction of tunnel entrance slope based on LSSVM and bacterial foraging optimization algorithm
W Xihao, B Zhiyu, L Yuedong, W Yuchao, K Song - Scientific Reports, 2024 - nature.com
In order to realize the effective prediction of landslide risk in the tunnel entrance area, an
multivariate time series model is established on the basis of the traditional model, taking …
multivariate time series model is established on the basis of the traditional model, taking …
On linear model with markov signal priors
LV Truong - International Conference on Artificial …, 2022 - proceedings.mlr.press
In this paper, we estimate free energy, average mutual information, and minimum mean
square error (MMSE) of a linear model under the assumption that the source is generated by …
square error (MMSE) of a linear model under the assumption that the source is generated by …
Proximal gradient algorithm with dual momentum for robust compressive sensing MRI
Z Xie, L Liu, Z Chen, C Wang - Signal Processing, 2025 - Elsevier
Adopting the new signal acquisition technology Compressive Sensing (CS) to Magnetic
Resonance Imaging (MRI) reconstruction has been proved to be an effective scheme for …
Resonance Imaging (MRI) reconstruction has been proved to be an effective scheme for …
A Non-asymptotic Analysis of Generalized Vector Approximate Message Passing Algorithms with Rotationally Invariant Designs
C Cademartori, C Rush - IEEE Transactions on Information …, 2024 - ieeexplore.ieee.org
Approximate Message Passing (AMP) algorithms are a class of iterative procedures for
computationally-efficient estimation in high-dimensional inference and estimation tasks. Due …
computationally-efficient estimation in high-dimensional inference and estimation tasks. Due …
Improved bounds for the many-user MAC
SS Kowshik - 2022 IEEE International Symposium on …, 2022 - ieeexplore.ieee.org
Many-user MAC is an important model for understanding energy efficiency of massive
random access in 5G and beyond. Introduced in Polyanskiy'2017 for the AWGN channel …
random access in 5G and beyond. Introduced in Polyanskiy'2017 for the AWGN channel …
Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing
We consider the problem of localizing change points in high-dimensional linear regression.
We propose an Approximate Message Passing (AMP) algorithm for estimating both the …
We propose an Approximate Message Passing (AMP) algorithm for estimating both the …