Works (7)

Updated: July 5th, 2023 15:41

2021 article

Local Convergence of an AMP Variant to the LASSO Solution in Finite Dimensions

2021 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), pp. 2256–2261.

By: Y. Ma*, M. Kang n, J. Silversteint & D. Baron n

TL;DR: It is shown that whenever the AMP variant converges, it converges to the LASSO solution for arbitrary finite dimensional regression matrices and that the original AMP, which is a special case of the proposed AMP variants, is locally stable around the LassO solution. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: October 26, 2021

2019 article

Analysis of Approximate Message Passing With Non-Separable Denoisers and Markov Random Field Priors

Ma, Y., Rush, C., & Baron, D. (2019, November). IEEE TRANSACTIONS ON INFORMATION THEORY, Vol. 65, pp. 7367–7389.

By: Y. Ma n, C. Rush* & D. Baron n

author keywords: Approximation algorithms; Task analysis; Approximate message passing; non-separable denoiser; Markov random field; finite sample analysis
TL;DR: A rigorous analysis of the performance of AMP is provided, demonstrating the accuracy of the state evolution predictions, when a class of non-separable sliding-window denoisers is applied. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: February 3, 2020

2017 conference paper

Analysis of approximate message passing with a class of non-separable denoisers

2017 ieee international symposium on information theory (isit), 231–235.

By: Y. Ma n, C. Rush* & D. Baron n

TL;DR: It is proved that a new form of state evolution still accurately predicts AMP performance, using a class of non-separable sliding-window denoisers, which will lead to a characterization of more general denoiser in problems including compressive image reconstruction. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2017 conference paper

Fusion of multi-angular aerial images based on epipolar geometry and matrix completion

2017 24th ieee international conference on image processing (icip), 1197–1201.

By: Y. Ma, D. Liu, H. Mansour, U. Kamilov, Y. Taguchi, P. Boufounos, A. Vetro

Source: NC State University Libraries
Added: August 6, 2018

2016 journal article

Compressive Hyperspectral Imaging via Approximate Message Passing

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 10(2), 389–401.

By: J. Tan n, Y. Ma n, H. Rueda*, D. Baron n & G. Arce*

author keywords: Approximate message passing; CASSI; compressive hyperspectral imaging; gradient projection for sparse reconstruction; image denoising; two-step iterative shrinkage/thresholding; Wiener filtering
TL;DR: The adaptive Wiener filter is modified and employed to solve for the divergence issue of AMP, and the numerical experiments show that AMP-3D-Wiener outperforms existing widely-used algorithms such as gradient projection for sparse reconstruction (GPSR) and two-step iterative shrinkage/thresholding (TwIST) given a similar amount of runtime. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

2015 conference paper

Mismatched estimation in large linear systems

2015 ieee international symposium on information theory (isit), 760–764.

By: Y. Ma n, D. Baron n & A. Beirami*

TL;DR: This work focuses on large linear systems where the measurements are acquired via an independent and identically distributed random matrix, and are corrupted by additive white Gaussian noise. (via Semantic Scholar)
Sources: NC State University Libraries, ORCID
Added: August 6, 2018

2014 journal article

Two-Part Reconstruction With Noisy-Sudocodes

IEEE TRANSACTIONS ON SIGNAL PROCESSING, 62(23), 6323–6334.

By: Y. Ma n, D. Baron n & D. Needell*

author keywords: Compressed sensing; two-part reconstruction; 1-bit CS
TL;DR: This work proposes a Noisy-Sudocodes algorithm that performs two-part reconstruction of sparse signals in the presence of measurement noise and provides a theoretical analysis that characterizes the trade-off between runtime and reconstruction quality. (via Semantic Scholar)
Sources: Web Of Science, ORCID
Added: August 6, 2018

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