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20242026
most citedNonparametric two-sample hypothesis testing for low-rank random graphs of differing sizes

6 citations · 6 across the 13 of their papers we have counts for

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7 papers · 1 filter

stat.ME2026

A functional tensor model for dynamic multilayer networks with common invariant subspaces and the RKHS estimation

Runshi Tang, Runbing Zheng, Anru R. Zhang +1

Dynamic multilayer networks are frequently used to describe the structure and temporal evolution of multiple relationships among common entities, with applications in fields such a…

stat.ME2026

When prompt perturbations break your A/B test: A valid statistical test for generative surveying

Hayden Helm, Carey Priebe

Generative surveying -- where collections of LLM-based personas provide feedback on messages -- has emerged as a cheap and scalable alternative to traditional market research. Howe…

stat.ME2026

Recovering manifold structure in LLM responses through a joint Euclidean mirror

Maximilian Baum, Aranyak Acharyya, Tianyi Chen +5

Understanding the behavior of black-box large language models and determining effective means of comparing their performance is a key task in modern machine learning. We consider h…

stat.ME2026

Multi-rank Subspace Change-point Detection with Application in Monitoring Robotic Swarms

Jonghyeok Lee, Yao Xie, Youngser Park +3

We study real-time detection of low-rank changes in the covariance structure of high-dimensional streaming data, motivated by robotic swarm monitoring. Building on the spiked covar…

stat.ME2026

Dynamic networks clustering via mirror distance

Runbing Zheng, Avanti Athreya, Marta Zlatic +2

The classification of different patterns of network evolution, for example in brain connectomes or social networks, is a key problem in network inference and modern data science. B…

stat.ME2025

Taming Variability: Randomized and Bootstrapped Conformal Risk Control for LLMs

Lingyou Pang, Lei Huang, Jianyu Lin +3

We transform the randomness of LLMs into precise assurances using an actuator at the API interface that applies a user-defined risk constraint in finite samples via Conformal Risk…