← 研踪 PaperTrailarXiv:2505.23565 · v2
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning
首次提交 2025-05-29 23:39
版本更新 2026-11-01 06:00
雷达观测 2026-11-04 23:43
摘要
We introduce dro, an open-source Python library for distributionally robust optimization (DRO) for regression and classification problems. The library implements 15 DRO formulations and 9 backbone models, enabling 85 distinct DRO methods. Furthermore, dro is compatible with both scikit-learn and PyTorch through a unified interface, and uses approximation techniques to reduce runtime for some computationally demanding formulations. Comprehensive documentation is available at https://python-dro.org.
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v2 · 2026-11-01 06:00 · 最新观测版本
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning
We introduce dro, an open-source Python library for distributionally robust optimization (DRO) for regression and classification problems. The library implements 15 DRO formulations and 9 backbone models, enabling 85 distinct DRO methods. Furthermore, dro is compatible with both scikit-learn and PyTorch through a unified interface, and uses approximation techniques to reduce runtime for some computationally demanding formulations. Comprehensive documentation is available at https://python-dro.org.
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