Trung Vu
Orcid: 0000-0003-2180-5994Affiliations:
- University of Maryland, Department of Computer Science and Electrical Engineering, MD, USA
- Oregon State University, School of Electrical Engineering and Computer Science, Corvallis, OR, USA (PhD 2022)
According to our database1,
Trung Vu
authored at least 22 papers
between 2018 and 2024.
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Bibliography
2024
Constrained Independent Vector Analysis With Reference for Multi-Subject fMRI Analysis.
IEEE Trans. Biomed. Eng., December, 2024
Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks.
Proceedings of the IEEE International Conference on Acoustics, 2024
A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis.
Proceedings of the IEEE International Conference on Acoustics, 2024
Proceedings of the IEEE International Conference on Acoustics, 2024
Reproducibility and Replicability in Neuroimaging: Constrained IVA as an Effective Assessment Tool.
Proceedings of the 32nd European Signal Processing Conference, 2024
2023
A closed-form bound on the asymptotic linear convergence of iterative methods via fixed point analysis.
Optim. Lett., April, 2023
Sensors, March, 2023
On Local Linear Convergence of Projected Gradient Descent for Unit-Modulus Least Squares.
IEEE Trans. Signal Process., 2023
ON THE ASYMPTOTIC LINEAR CONVERGENCE OF GRADIENT DESCENT FOR NON-SYMMETRIC MATRIX COMPLETION.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023
Constrained Independent Vector Analysis with References: Algorithms and Performance Evaluation.
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023
Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023
2022
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares.
IEEE Trans. Signal Process., 2022
On Local Linear Convergence Rate of Iterative Hard Thresholding for Matrix Completion.
IEEE Trans. Signal Process., 2022
2021
CoRR, 2021
A Closed-Form Bound on Asymptotic Linear Convergence of Positively Quadratic First-Order Difference Equations.
CoRR, 2021
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent.
Proceedings of the IEEE International Conference on Acoustics, 2021
2020
A Novel Attribute-Based Symmetric Multiple Instance Learning for Histopathological Image Analysis.
IEEE Trans. Medical Imaging, 2020
Perturbation expansions and error bounds for the truncated singular value decomposition.
CoRR, 2020
2019
ON Convergence of Projected Gradient Descent for Minimizing a Large-Scale Quadratic Over the Unit Sphere.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019
Local Convergence of the Heavy Ball Method in Iterative Hard Thresholding for Low-rank Matrix Completion.
Proceedings of the IEEE International Conference on Acoustics, 2019
Accelerating Iterative Hard Thresholding for Low-rank Matrix Completion via Adaptive Restart.
Proceedings of the IEEE International Conference on Acoustics, 2019
2018
Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018