Stochastic Approximation Approaches to Group Distributionally Robust Optimization and Beyond.
- DOI
- 10.1109/tpami.2026.3703554
- Published
- 2026 Oct
- 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.2026.3703554,
title = {Stochastic Approximation Approaches to Group Distributionally Robust Optimization and Beyond.},
author = {Zhang L and Bai H and Zhao P and Zhou ZH},
year = {2026},
journal = {IEEE transactions on pattern analysis and machine intelligence},
doi = {10.1109/tpami.2026.3703554},
url = {https://doi.org/10.1109/tpami.2026.3703554}
}RIS
TY - JOUR TI - Stochastic Approximation Approaches to Group Distributionally Robust Optimization and Beyond. AU - Zhang L AU - Bai H AU - Zhao P AU - Zhou ZH PY - 2026 JO - IEEE transactions on pattern analysis and machine intelligence DO - 10.1109/tpami.2026.3703554 UR - https://doi.org/10.1109/tpami.2026.3703554 ER -
APA
L, Z., H, B., P, Z., & ZH, Z. (2026). Stochastic Approximation Approaches to Group Distributionally Robust Optimization and Beyond.. IEEE transactions on pattern analysis and machine intelligence. https://doi.org/10.1109/tpami.2026.3703554
Source records
- pubmed · retrieved 2026-09-25T07:19:34.710Z