covariate shift
A situation where the distribution of the input data changes between training and testing phases, which can lead to model performance degradation if not addressed.
- A Unified Framework for the Transportability of Population-Level Causal Measures
- Adjusted Count Quantification Learning on Graphs
- Computational Efficiency under Covariate Shift in Kernel Ridge Regression
- Conformal Inference under High-Dimensional Covariate Shifts via Likelihood-Ratio Regularization
- Estimating Model Performance Under Covariate Shift Without Labels
- Graph Data Selection for Domain Adaptation: A Model-Free Approach
- Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution
- Vicinal Label Supervision for Reliable Aleatoric and Epistemic Uncertainty Estimation