Neurodynamic Approaches with Fixed-Step Optimality for Rank Minimization: A Data-Driven Framework.
- DOI
- 10.1109/tpami.2026.3717777
- Published
- 2026 Jul 28
- Container
- IEEE transactions on pattern analysis and machine intelligence
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tpami.2026.3717777,
title = {Neurodynamic Approaches with Fixed-Step Optimality for Rank Minimization: A Data-Driven Framework.},
author = {Zhang M and He X and Zhao Y and Huang T and Yu J},
year = {2026},
journal = {IEEE transactions on pattern analysis and machine intelligence},
doi = {10.1109/tpami.2026.3717777},
url = {https://doi.org/10.1109/tpami.2026.3717777}
}RIS
TY - JOUR TI - Neurodynamic Approaches with Fixed-Step Optimality for Rank Minimization: A Data-Driven Framework. AU - Zhang M AU - He X AU - Zhao Y AU - Huang T AU - Yu J PY - 2026 JO - IEEE transactions on pattern analysis and machine intelligence DO - 10.1109/tpami.2026.3717777 UR - https://doi.org/10.1109/tpami.2026.3717777 ER -
APA
M, Z., X, H., Y, Z., T, H., & J, Y. (2026). Neurodynamic Approaches with Fixed-Step Optimality for Rank Minimization: A Data-Driven Framework.. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/tpami.2026.3717777
Source records
- pubmed · retrieved 2026-09-25T23:22:23.966Z