Poster "distributionally robust optimization" Papers

23 papers found

An Effective Manifold-based Optimization Method for Distributionally Robust Classification

Jiawei Huang, Hu Ding

ICLR 2025

Bootstrap Your Uncertainty: Adaptive Robust Classification Driven by Optimal-Transport

Jiawei Huang, Minming Li, Hu Ding

NEURIPS 2025

Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping

Guangyi Liu, Suzan Iloglu, Michael Caldara et al.

ICML 2025arXiv:2503.09755
3
citations

Distributionally Robust Performative Optimization

Zhuangzhuang Jia, Yijie Wang, Roy Dong et al.

NEURIPS 2025arXiv:2407.01344
2
citations

Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty

Xu Wan, Chao Yang, Cheng Yang et al.

NEURIPS 2025

Group Distributionally Robust Dataset Distillation with Risk Minimization

Saeed Vahidian, Mingyu Wang, Jianyang Gu et al.

ICLR 2025arXiv:2402.04676
9
citations

Improved Diffusion-based Generative Model with Better Adversarial Robustness

Zekun Wang, Mingyang Yi, Shuchen Xue et al.

ICLR 2025arXiv:2502.17099
1
citations

Revisiting Large-Scale Non-convex Distributionally Robust Optimization

Qi Zhang, Yi Zhou, Simon Khan et al.

ICLR 2025
1
citations

Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control

Gezheng Xu, Hui GUO, Li Yi et al.

ICLR 2025
5
citations

Universal generalization guarantees for Wasserstein distributionally robust models

Tam Le, Jerome Malick

ICLR 2025arXiv:2402.11981
7
citations

Criterion Collapse and Loss Distribution Control

Matthew J. Holland

ICML 2024arXiv:2402.09802
2
citations

Differentiable Distributionally Robust Optimization Layers

Xutao Ma, Chao Ning, WenLi Du

ICML 2024arXiv:2406.16571
8
citations

Distributionally Robust Data Valuation

Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu et al.

ICML 2024

Distributionally Robust Loss for Long-Tailed Multi-Label Image Classification

Dekun Lin, Zhe Cui, Rui Chen et al.

ECCV 2024
10
citations

Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond

Dingzhi Yu, Yunuo Cai, Wei Jiang et al.

ICML 2024arXiv:2403.03562
7
citations

Efficient Stochastic Approximation of Minimax Excess Risk Optimization

Lijun Zhang, Haomin Bai, Wei-Wei Tu et al.

ICML 2024arXiv:2306.00026
4
citations

Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications

Jiashuo Liu, Jiayun Wu, Tianyu Wang et al.

ICML 2024arXiv:2311.05054
5
citations

Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data

Kishan Panaganti, Adam Wierman, Eric Mazumdar

ICML 2024

On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity

Junyi FAN, Yuxuan Han, Zijian Liu et al.

ICML 2024

Robust Data-driven Prescriptiveness Optimization

Mehran Poursoltani, Erick Delage, Angelos Georghiou

ICML 2024arXiv:2306.05937
2
citations

Statistical Properties of Robust Satisficing

zhiyi li, Yunbei Xu, Ruohan Zhan

ICML 2024arXiv:2405.20451

The Role of Learning Algorithms in Collective Action

Omri Ben-Dov, Jake Fawkes, Samira Samadi et al.

ICML 2024arXiv:2405.06582
10
citations

To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO

Zi-Hao Qiu, Siqi Guo, Mao Xu et al.

ICML 2024arXiv:2404.04575
10
citations