robust estimation
Robust estimation techniques are used to improve the performance of statistical models by minimizing the influence of outlier data points, ensuring that model predictions remain stable and accurate in the presence of noise.
- IDOL: Meeting Diverse Distribution Shifts with Prior Physics for Tropical Cyclone Multi-Task Estimation
- Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point
- Online robust locally differentially private learning for nonparametric regression
- Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means
- Robust Estimation Under Heterogeneous Corruption Rates