18 citations · 23 across the 14 of their papers we have counts for
8 papers · 1 filter
Not All Uncertainty Matters: Simulation-in-the-Loop Fast-Slow Reasoning for Decision-Critical Autonomous Driving System
Jiayi Chen, Shuai Wang, Guangxu Zhu +3
Large vision-language models (VLMs) provide powerful open-world perception and reasoning for autonomous driving, but their high computational cost and inference latency make contin…
The exact dimensional threshold for Spearman rank-correlation compatibility
Ruodu Wang, Zhenyuan Zhang
We show that, for a given dimension, the set of Spearman's rank correlation matrices and that of linear correlation matrices coincide if and only if the dimension is no larger than…
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)…
Admissibility and Complete Classes for False Discovery Rate Control with E-values
Liulei Sun, Ruodu Wang
The false discovery rate (FDR) is the most widely used error metric in modern multiple testing. We provide a comprehensive analysis of the admissibility of e-value-based procedures…
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 t…
Combining e-values using demi-supermartingales
Jiahao Ming, Aaditya Ramdas, Yi Shen +2
We present a new method for combining e-variables through demi-supermartingales, which settles an old conjecture in the literature on nonparametric mean testing. It also provides a…
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…
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…