robust learning

Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks AAAI 2024 Robust Learning via Conditional Prevalence Adjustment WACV 2024 Robust Reinforcement Learning from Corrupted Human Feedback NeurIPS 2024 Sample and Computationally Efficient Robust Learning of Gaussian Single-Index Models NeurIPS 2024 Testable Learning of General Halfspaces with Adversarial Label Noise COLT 2024 Wasserstein Distributionally Robust Optimization through the Lens of Structural Causal Models and Individual Fairness NeurIPS 2024 Adaptive Sample Selection for Robust Learning Under Label Noise WACV 2023 Adversarially Robust Learning with Tolerance ALT 2023 Adversarially Robust Learning with Uncertain Perturbation Sets NeurIPS 2023 Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise ICML 2023 Combating Bilateral Edge Noise for Robust Link Prediction NeurIPS 2023 Combating Unknown Bias with Effective Bias-Conflicting Scoring and Gradient Alignment AAAI 2023 Doubly-Robust Self-Training NeurIPS 2023 Efficient Testable Learning of Halfspaces with Adversarial Label Noise NeurIPS 2023 Explanation-based Finetuning Makes Models More Robust to Spurious Cues ACL 2023 GSLB: The Graph Structure Learning Benchmark NeurIPS 2023 Late Stopping: Avoiding Confidently Learning from Mislabeled Examples ICCV 2023 Learning From Noisy Labels With Decoupled Meta Label Purifier CVPR 2023 Meta Self-Refinement for Robust Learning with Weak Supervision EACL 2023 Multiple Robust Learning for Recommendation AAAI 2023 Noise Injection Node Regularization for Robust Learning ICLR 2023 Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning CVPR 2023 Reliable learning in challenging environments NeurIPS 2023 Robust Causal Graph Representation Learning against Confounding Effects AAAI 2023 Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy NeurIPS 2023