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From the 1 of 15 linked papers with an AI index.

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15 papers

math.ST2026

Gaffke's confidence interval for the mean of bounded data is inadmissible but asymptotically efficient

Jiahao Ming, Aaditya Ramdas, Yi Shen +2

Given observations , Gaffke (2005) defined \[ K_n(\mathbf x)=\mathbb{P}_{\mathbf D}\!\left\{\sum_{i=1}^n x_iD_i\le 1\right\}, \qquad (D_0,D_1,\ldots,D_n)…

stat.ME2026

Admissibility and Complete Classes for False Discovery Rate Control with E-values

Liulei Sun, Ruodu Wang

The paper analyzes the admissibility of e‑value based procedures for controlling the false discovery rate, showing that weighted‑mean e‑Benjamini‑Hochberg methods form a complete c…

math.PR2026

Quadratic-form Optimal Transport

Ruodu Wang, Zhenyuan Zhang

We introduce the framework of quadratic-form optimal transport (QOT), whose transport cost has the form for some coupling between tw…

stat.ML2026

Online monotone density estimation and log-optimal calibration

Rohan Hore, Ruodu Wang, Aaditya Ramdas

We study the problem of online monotone density estimation, where density estimators must be constructed in a predictable manner from sequentially observed data. We propose two onl…

stat.ME2026

Online LLM watermark detection via e-processes

Weijie Su, Ruodu Wang, Zinan Zhao

Watermarking for large language models (LLMs) has emerged as an effective tool for distinguishing AI-generated text from human-written content. Statistically, watermark schemes ind…

stat.ME2026

Tiny but uniform improvements of adaptive BH procedures via compound e-values

Nikolaos Ignatiadis, Ruodu Wang, Aaditya Ramdas

After the seminal Benjamini-Hochberg (BH) procedure for controlling the false discovery rate (FDR) was proposed, dozens of papers have attempted to improve its power by adapting to…