"distributionally robust optimization" Papers
29 papers found
Conference
An Effective Manifold-based Optimization Method for Distributionally Robust Classification
Jiawei Huang, Hu Ding
Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes
Yifan Lin, Enlu Zhou
Bootstrap Your Uncertainty: Adaptive Robust Classification Driven by Optimal-Transport
Jiawei Huang, Minming Li, Hu Ding
Designing Ambiguity Sets for Distributionally Robust Optimization Using Structural Causal Optimal Transport
Ahmad Reza Ehyaei, Golnoosh Farnadi, Samira Samadi
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara et al.
Distributionally Robust Performative Optimization
Zhuangzhuang Jia, Yijie Wang, Roy Dong et al.
Fuz-RL: A Fuzzy-Guided Robust Framework for Safe Reinforcement Learning under Uncertainty
Xu Wan, Chao Yang, Cheng Yang et al.
Group Distributionally Robust Dataset Distillation with Risk Minimization
Saeed Vahidian, Mingyu Wang, Jianyang Gu et al.
Improved Diffusion-based Generative Model with Better Adversarial Robustness
Zekun Wang, Mingyang Yi, Shuchen Xue et al.
Revisiting Large-Scale Non-convex Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Simon Khan et al.
Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control
Gezheng Xu, Hui GUO, Li Yi et al.
Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval
Guangyuan Ma, Yongliang Ma, Xing Wu et al.
Universal generalization guarantees for Wasserstein distributionally robust models
Tam Le, Jerome Malick
Criterion Collapse and Loss Distribution Control
Matthew J. Holland
Differentiable Distributionally Robust Optimization Layers
Xutao Ma, Chao Ning, WenLi Du
Distributionally Robust Data Valuation
Xiaoqiang Lin, Xinyi Xu, Zhaoxuan Wu et al.
Distributionally Robust Loss for Long-Tailed Multi-Label Image Classification
Dekun Lin, Zhe Cui, Rui Chen et al.
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond
Dingzhi Yu, Yunuo Cai, Wei Jiang et al.
Efficient Stochastic Approximation of Minimax Excess Risk Optimization
Lijun Zhang, Haomin Bai, Wei-Wei Tu et al.
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
Jiashuo Liu, Jiayun Wu, Tianyu Wang et al.
Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization
Qi Zhang, Yi Zhou, Ashley Prater-Bennette et al.
Model-Free Robust $\phi$-Divergence Reinforcement Learning Using Both Offline and Online Data
Kishan Panaganti, Adam Wierman, Eric Mazumdar
On the Convergence of Projected Bures-Wasserstein Gradient Descent under Euclidean Strong Convexity
Junyi FAN, Yuxuan Han, Zijian Liu et al.
Robust Data-driven Prescriptiveness Optimization
Mehran Poursoltani, Erick Delage, Angelos Georghiou
Statistical Properties of Robust Satisficing
zhiyi li, Yunbei Xu, Ruohan Zhan
Temporally and Distributionally Robust Optimization for Cold-Start Recommendation
Xinyu Lin, Wenjie Wang, Jujia Zhao et al.
The Role of Learning Algorithms in Collective Action
Omri Ben-Dov, Jake Fawkes, Samira Samadi et al.
To Cool or not to Cool? Temperature Network Meets Large Foundation Models via DRO
Zi-Hao Qiu, Siqi Guo, Mao Xu et al.
Trust Region Methods for Nonconvex Stochastic Optimization beyond Lipschitz Smoothness
Chenghan Xie, Chenxi Li, Chuwen Zhang et al.