conftrace_

distributional robustness

29 papers

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Also known as

DR

Co-occurring keywords

distribution shift (722) markov decision process (790) adversarial training (1262) domain generalization (1522) wasserstein distance (417) group fairness (158) adversarial example (564) neural network (6616) minimax optimization (186) sample complexity (1169)

Papers

Identifying and Mitigating Spurious Correlation in Multi-Task Learning CVPR 2025
Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms NIPS 2024
Achieving Group Distributional Robustness and Minimax Group Fairness with Interpolating Classifiers AISTATS 2024
PRASS: Probabilistic Risk-averse Robust Learning with Stochastic Search IJCAI 2024
DRF: Improving Certified Robustness via Distributional Robustness Framework AAAI 2024
Sample Complexity of Variance-Reduced Distributionally Robust Q-Learning JMLR 2024
Generative Data Augmentation using LLMs improves Distributional Robustness in Question Answering EACL 2024
Achievable distributional robustness when the robust risk is only partially identified NIPS 2024
Optimal Transport Model Distributional Robustness NIPS 2023
Wasserstein distributional robustness of neural networks NIPS 2023
The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model NIPS 2023
Group Distributionally Robust Reinforcement Learning with Hierarchical Latent Variables AISTATS 2023
Global-Local Regularization Via Distributional Robustness AISTATS 2023
Certifying Some Distributional Fairness with Subpopulation Decomposition NIPS 2022
Methods for Estimating and Improving Robustness of Language Models NAACL 2022
Exploring The Landscape of Distributional Robustness for Question Answering Models EMNLP 2022
CyCLIP: Cyclic Contrastive Language-Image Pretraining NIPS 2022
Certifying Out-of-Domain Generalization for Blackbox Functions ICML 2022
Distributionally Adaptive Meta Reinforcement Learning NIPS 2022
Explicit Tradeoffs between Adversarial and Natural Distributional Robustness NIPS 2022
Data Determines Distributional Robustness in Contrastive Language Image Pre-training (CLIP) ICML 2022
FOCUS: Familiar Objects in Common and Uncommon Settings ICML 2022
Generalised Lipschitz Regularisation Equals Distributional Robustness ICML 2021
Distributional Robustness Loss for Long-Tail Learning ICCV 2021
Evaluating model performance under worst-case subpopulations NIPS 2021