3 papers
stat.ML2025
A PyTorch Framework for Scalable Non-Crossing Quantile Regression
Kaihua Chang
Quantile regression is fundamental to distributional modeling, yet independent estimation of multiple quantiles frequently produces crossing -- where estimated quantile functions v…
stat.ML2025
Extreme Event Aware (-) Learning
Kai Chang, Themistoklis P. Sapsis
Quantifying and predicting rare and extreme events is challenging because such events are infrequent, severe, and expensive to simulate. Existing data-driven methods often require…
cs.CV2024
Theoretical Analysis for Expectation-Maximization-Based Multi-Model 3D Registration
David Jin, Harry Zhang, Kai Chang
We perform detailed theoretical analysis of an expectation-maximization-based algorithm recently proposed in for solving a variation of the 3D registration problem, named multi-mod…