distribution shift

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering ICML 2024 Few-shot Adaptation to Distribution Shifts By Mixing Source and Target Embeddings ICML 2024 f-FERM: A Scalable Framework for Robust Fair Empirical Risk Minimization ICLR 2024 Generalize or Detect? Towards Robust Semantic Segmentation Under Multiple Distribution Shifts NeurIPS 2024 Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks ICML 2024 GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts NeurIPS 2024 Gradual Optimization Learning for Conformational Energy Minimization ICLR 2024 GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts NeurIPS 2024 How Does Unlabeled Data Provably Help Out-of-Distribution Detection? ICLR 2024 How safe am I given what I see? Calibrated prediction of safety chances for image-controlled autonomy L4DC 2024 How to Fine-Tune Vision Models with SGD ICLR 2024 How to Fix a Broken Confidence Estimator: Evaluating Post-hoc Methods for Selective Classification with Deep Neural Networks UAI 2024 Implicit and Explicit Policy Constraints for Offline Reinforcement Learning CLeaR 2024 Improving Domain Generalization with Domain Relations ICLR 2024 Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting ICML 2024 Improving self-training under distribution shifts via anchored confidence with theoretical guarantees NeurIPS 2024 Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation CVPR 2024 IW-GAE: Importance weighted group accuracy estimation for improved calibration and model selection in unsupervised domain adaptation ICML 2024 Keeping LLMs Aligned After Fine-tuning: The Crucial Role of Prompt Templates NeurIPS 2024 Label Alignment Regularization for Distribution Shift JMLR 2024 LatentDR: Improving Model Generalization Through Sample-Aware Latent Degradation and Restoration WACV 2024 Latent Representation Entropy Density for Distribution Shift Detection UAI 2024 Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time ICLR 2024 Learning Distributionally Robust Tractable Probabilistic Models in Continuous Domains UAI 2024 Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds COLT 2024