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20242026
most citedFrom Sparse to Dense Functional Data: Phase Transitions from a Simultaneous Inference Perspective

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cs.LG2026

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

Ruishuo Chen, Weijia Li, Xun Wang +3

In ecology, psychometrics, and the analysis of social and financial networks, binary matrices are often analyzed conditional on their observed row and column sums, which restricts…

stat.ME2026

Asymptotic Anytime-Valid Quantile Inference under Local Differential Privacy

Leheng Cai, Qirui Hu, Shuyuan Wu

Sequential quantile inference is difficult under local differential privacy because every record is randomized before reaching the analyst and the limiting quantile variance depend…

math.ST2026

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

Leheng Cai, Qirui Hu

We study simultaneous inference for maxima of canonical order-two -statistics in high dimension. Degeneracy makes quadratic fluctuations leading, so ordinary Gaussian calibratio…

stat.ME2026

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

Leheng Cai, Zhou Zhou

We develop bootstrap-assisted robust binary segmentation (BARBS), a recursive binary segmentation method for multiple change point detection under general nonstationary temporal dy…

math.ST2026

Asymptotic Anytime-Valid Inference for U-statistics

Leheng Cai, Qirui Hu, Weijia Li

We study asymptotic anytime-valid confidence sequences for degree-two U-statistics under continuous monitoring. In the nondegenerate case, Hoeffding's projection reduces the proble…

math.ST2026

Strong Gaussian approximation for U-statistics in high dimensions and beyond

Weijia Li, Leheng Cai, Qirui Hu

We establish a strong Gaussian approximation for high-dimensional non-degenerate U-statistics with diverging dimension. Under mild assumptions, we construct, on a sufficiently rich…