Distribution Shift

Frequency Shuffling and Enhancement for Open Set Recognition AAAI 2024 GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts NeurIPS 2024 Gradual Domain Adaptation via Manifold-Constrained Distributionally Robust Optimization NeurIPS 2024 How to Handle Different Types of Out-of-Distribution Scenarios in Computational Argumentation? A Comprehensive and Fine-Grained Field Study ACL 2024 Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization AAAI 2024 LaSCal: Label-Shift Calibration without target labels NeurIPS 2024 Learning a Single Neuron Robustly to Distributional Shifts and Adversarial Label Noise NeurIPS 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 Learning to Reweight for Generalizable Graph Neural Network AAAI 2024 MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts NeurIPS 2024 MaxEnt Loss: Calibrating Graph Neural Networks under Out-of-Distribution Shift (Student Abstract) AAAI 2024 Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift ICLR 2024 Mitigating Covariate Shift in Misspecified Regression with Applications to Reinforcement Learning COLT 2024 Multimodal Graph Neural Architecture Search under Distribution Shifts AAAI 2024 Non-Exchangeable Conformal Risk Control ICLR 2024 On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift NeurIPS 2024 On the Generalization of Training-based ChatGPT Detection Methods EMNLP 2024 Optimal Aggregation of Prediction Intervals under Unsupervised Domain Shift NeurIPS 2024 Optimal Classification under Performative Distribution Shift NeurIPS 2024 Performative Reinforcement Learning in Gradually Shifting Environments UAI 2024 Protected Test-Time Adaptation via Online Entropy Matching: A Betting Approach NeurIPS 2024 Rethinking Score Distillation as a Bridge Between Image Distributions NeurIPS 2024 Revealing Distribution Discrepancy by Sampling Transfer in Unlabeled Data NeurIPS 2024 Self-Healing Machine Learning: A Framework for Autonomous Adaptation in Real-World Environments NeurIPS 2024