A package of distributionally robust optimization (DRO) methods. Implemented via cvxpy and PyTorch
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Updated
May 31, 2025 - Jupyter Notebook
A package of distributionally robust optimization (DRO) methods. Implemented via cvxpy and PyTorch
[NeurIPS2023] Official code of "Understanding Contrastive Learning via Distributionally Robust Optimization"
The Pytorch implementation for "Topology-aware Robust Optimization for Out-of-Distribution Generalization" (ICLR 2023)
"Aligning Distributionally Robust Optimization with Practical Deep Learning Needs"
[ICLR 2025] Official code of "Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization"
Distributionally robust machine learning with Pytorch and Scikit-learn wrappers
Temporally and Distributionally Robust Optimization for Cold-start Recommendation (AAAI'24)
[ICDE2024] Official code of "BSL: Understanding and Improving Softmax Loss for Recommendation"
Python Implementation of the Instance-wise Distributionally Robust Nonnegative Matrix Factorization (iDRNMF)
This is the official repository for the ICLR 2024 paper Out-Of-Domain Unlabeled Data Improves Generalization.
Code for the experiments in the paper "Contextual Robust Optimisation with Uncertainty Quantification".
Code for the Paper "Robust Offline Reinforcement Learning with Linearly Structured f-Divergence Regularization", International Conference on Machine Learning (ICML) 2025
this repository hosts my master's thesis codes and dataset.
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