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ORCIDTrung Vu 0001
Person information
- affiliation: University of Maryland, Department of Computer Science and Electrical Engineering, MD, USA
- affiliation (PhD 2022): Oregon State University, School of Electrical Engineering and Computer Science, Corvallis, OR, USA
Other persons with the same name
- Trung Vu — disambiguation page
- Trung Vu 0002
![[0000-0002-9038-4620]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0002-9038-4620")
— Google, USA
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2020 – today
- 2025
[j10]Hanlu Yang, Trung Vu, Ehsan Ahmed Dhrubo, Vince D. Calhoun, Tülay Adali:
A Flexible Constrained ICA Approach for Multisubject fMRI Analysis. Int. J. Biomed. Imaging 2025(1) (2025)- [j9]Ben Gabrielson, Hanlu Yang, Trung Vu, Vince D. Calhoun, Tülay Adali:
Large-Scale Independent Vector Analysis (IVA-G) via Coresets. IEEE Trans. Signal Process. 73: 230-244 (2025) - [c14]Chunying Jia, Weixin Wang, Trung Vu, Hanlu Yang, Ben Gabrielson, Vince D. Calhoun, Tülay Adali:
Adaptive Constrained ICA with Mixing Matrix Column Constraints: Application to fMRI Data. CISS 2025: 1-6 - [c13]Emin Erdem Kumbasar, Hanlu Yang, Trung Vu, Vince D. Calhoun, Tülay Adali:
Fusion of Multitask fMRI Data with Constrained Independent Vector Analysis. CISS 2025: 1-6 - 2024
- [j8]Ben Gabrielson, Hanlu Yang, Trung Vu, Vince D. Calhoun, Tülay Adali:
Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis. IEEE Access 12: 192356-192376 (2024) - [j7]Trung Vu, Francisco Laport, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Constrained Independent Vector Analysis With Reference for Multi-Subject fMRI Analysis. IEEE Trans. Biomed. Eng. 71(12): 3531-3542 (2024) - [c12]Francisco Laport, Adriana Dapena, Trung Vu, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Reproducibility and Replicability in Neuroimaging: Constrained IVA as an Effective Assessment Tool. EUSIPCO 2024: 802-806 - [c11]Trung Vu, Hanlu Yang, Francisco Laport, Ben Gabrielson, Vince D. Calhoun, Tülay Adali:
A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis. ICASSP 2024: 1831-1835 - [c10]Hanlu Yang, Meiby Ortiz-Bouza, Trung Vu, Francisco Laport, Vince D. Calhoun, Selin Aviyente, Tülay Adali:
Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks. ICASSP 2024: 2141-2145 - [c9]Matthew Callahan, Trung Vu, Raviv Raich:
Provable Randomized Coordinate Descent for Matrix Completion. ICASSP 2024: 9421-9425 - 2023
- [j6]Trung Vu, Raviv Raich:
A closed-form bound on the asymptotic linear convergence of iterative methods via fixed point analysis. Optim. Lett. 17(3): 643-656 (2023) - [j5]Hanlu Yang, Trung Vu, Qunfang Long, Vince D. Calhoun, Tülay Adali:
Identification of Homogeneous Subgroups from Resting-State fMRI Data. Sensors 23(6): 3264 (2023) - [j4]Trung Vu, Raviv Raich, Xiao Fu:
On Local Linear Convergence of Projected Gradient Descent for Unit-Modulus Least Squares. IEEE Trans. Signal Process. 71: 3883-3897 (2023) - [c8]Trung Vu, Francisco Laport, Hanlu Yang, Tülay Adali:
Constrained Independent Vector Analysis with References: Algorithms and Performance Evaluation. ACSSC 2023: 827-831 - [c7]Trung Vu, Raviv Raich:
ON THE ASYMPTOTIC LINEAR CONVERGENCE OF GRADIENT DESCENT FOR NON-SYMMETRIC MATRIX COMPLETION. ACSSC 2023: 1049-1053 - [c6]Francisco Laport, Trung Vu, Hanlu Yang, Vince D. Calhoun, Tülay Adali:
Reproducibility in Joint Blind Source Separation: Application to fMRI Analysis. ACSSC 2023: 1448-1452 - 2022
- [j3]Trung Vu, Raviv Raich:
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares. IEEE Trans. Signal Process. 70: 4061-4076 (2022) - [j2]Trung Vu, Evgenia Chunikhina, Raviv Raich:
On Local Linear Convergence Rate of Iterative Hard Thresholding for Matrix Completion. IEEE Trans. Signal Process. 70: 5940-5953 (2022) - 2021
- [c5]Trung Vu, Raviv Raich:
Exact Linear Convergence Rate Analysis for Low-Rank Symmetric Matrix Completion via Gradient Descent. ICASSP 2021: 3240-3244 - [i4]Trung Vu, Raviv Raich:
A Closed-Form Bound on Asymptotic Linear Convergence of Positively Quadratic First-Order Difference Equations. CoRR abs/2112.10598 (2021) - [i3]Trung Vu, Raviv Raich:
On Asymptotic Linear Convergence of Projected Gradient Descent for Constrained Least Squares. CoRR abs/2112.11760 (2021) - [i2]Trung Vu, Raviv Raich:
On Local Convergence of Iterative Hard Thresholding for Matrix Completion. CoRR abs/2112.14733 (2021) - 2020
- [j1]Trung Vu, Phung Lai, Raviv Raich, Anh T. Pham, Xiaoli Z. Fern, Arvind U. K. Rao:
A Novel Attribute-Based Symmetric Multiple Instance Learning for Histopathological Image Analysis. IEEE Trans. Medical Imaging 39(10): 3125-3136 (2020) - [i1]Trung Vu, Evgenia Chunikhina, Raviv Raich:
Perturbation expansions and error bounds for the truncated singular value decomposition. CoRR abs/2009.07542 (2020)
2010 – 2019
- 2019
- [c4]Trung Vu, Raviv Raich:
Accelerating Iterative Hard Thresholding for Low-rank Matrix Completion via Adaptive Restart. ICASSP 2019: 2917-2921 - [c3]Trung Vu, Raviv Raich:
Local Convergence of the Heavy Ball Method in Iterative Hard Thresholding for Low-rank Matrix Completion. ICASSP 2019: 3417-3421 - [c2]Trung Vu, Raviv Raich, Xiao Fu:
ON Convergence of Projected Gradient Descent for Minimizing a Large-Scale Quadratic Over the Unit Sphere. MLSP 2019: 1-6 - 2018
- [c1]Trung Vu, Raviv Raich:
Adaptive Step Size Momentum Method For Deconvolution. SSP 2018: 438-442
Coauthor Index
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