Author

Le-Heng Cai

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Preprint Sep 2026

Asymptotic Anytime-Valid Quantile Inference under Local Differential Privacy

Sequential quantile inference is difficult under local differential privacy because every record is randomized before reaching the analyst and the limiting quantile variance depends on an unknown density. We develop an online procedure that combines randomized response with dynamically chained parallel stochastic gradi...

Le-Heng Cai, Qi-Rui Hu, Shu-Yuan Wu · 0 citations

Preprint Aug 2026

Recursive Multiple Change Point Detection of Nonstationary Time Series: Instability Tests, Estimation and Confidence Intervals

We develop bootstrap-assisted robust binary segmentation (BARBS), a recursive binary segmentation method for multiple change point detection under general nonstationary temporal dynamics. A novel Gaussian multiplier bootstrap for the CUSUM statistics is proposed, offering robustness to complex dependence structures. Th...

Le-Heng Cai, Zhou Zhou · 0 citations

#machine learning Preprint Sep 2026

One Proposal for Every Margin: Zero-Shot Amortized Sequential Importance Sampling for Binary Matrices

The proposed MarginFlow framework is a framework that turns the design of the proposal into a learning problem and amortizes it across margins by exploiting their self-similarity.

Rui-Shuo Chen, Wei-Jian Li, Xun Wang et al. · 0 citations

Preprint Sep 2026

Approximation Theorems for High-Dimensional Canonical U-Statistics: Gaussian Chaos and Phase Transition

We study simultaneous inference for maxima of canonical order-two $U$-statistics in high dimension. Degeneracy makes quadratic fluctuations leading, so ordinary Gaussian calibration can fail even after exact variance normalization. We show that the appropriate general target is a joint signed Gaussian quadratic chaos a...

Le-Heng Cai, Qi-Rui Hu · 0 citations