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20242026
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cs.DS2025

Uniformity Testing under User-Level Local Privacy

Clément L. Canonne, Abigail Gentle, Vikrant Singhal

We initiate the study of distribution testing under \emph{user-level} local differential privacy, where each of users contributes samples from the unknown underlying distri…

cs.LG2025

NashPG: A Policy Gradient Method with Iteratively Refined Regularization for Finding Nash Equilibria

Eason Yu, Tzu Hao Liu, Clément L. Canonne +4

Finding Nash equilibria in two-player zero-sum imperfect-information games remains a central challenge in multi-agent reinforcement learning. Recent multi-round regularization meth…

cs.DS2025

Instance-Optimal Uniformity Testing and Tracking

Guy Blanc, Clément L. Canonne, Erik Waingarten

In the uniformity testing task, an algorithm is provided with samples from an unknown probability distribution over a (known) finite domain, and must decide whether it is the unifo…

cs.LG2025

Zero-Shot Attribution for Large Language Models: A Distribution Testing Approach

Clément L. Canonne, Yash Pote, Uddalok Sarkar

A growing fraction of all code is sampled from Large Language Models (LLMs). We investigate the problem of attributing code generated by language models using hypothesis testing to…

math.ST2025

Gaussian Mean Testing under Truncation

Clément L. Canonne, Themis Gouleakis, Yuhao Wang +1

We consider the task of Gaussian mean testing, that is, of testing whether a high-dimensional vector perturbed by white noise has large magnitude, or is the zero vector. This quest…