collaborators

9 papers

math.PR2026

A Sharper Hoeffding Bound for Weighted Sums of Exchangeable Random Variables

Seongchan Lee, Ilmun Kim

We prove a Hoeffding-type moment generating function bound for weighted sums of bounded exchangeable random variables centered by their finite-population average. The bound improve…

math.ST2026

Sharp Minimax Rates for Smooth Two-Sample Testing under Central Differential Privacy

Ilmun Kim

We establish sharp minimax limits for two-sample testing of Hölder-smooth densities under central differential privacy. Given two independent samples, the goal is to decide whethe…

stat.ME2026

Aggregation of Statistical Evidence under Exchangeability

Antonin Schrab, Rajen Shah, Arthur Gretton +1

We study aggregation of statistical evidence under unknown and potentially complex dependence using group-invariance. Building on permutation-based constructions that treat transfo…

math.ST2026

High-Confidence Minimax Testing with Prescribed Errors

Ilmun Kim

Classical minimax lower bounds for testing are typically derived for fixed error probabilities, while high-confidence results often impose a common failure probability. We study pr…

stat.ML2026

Computational-Statistical Trade-off in Kernel Two-Sample Testing with Random Fourier Features

Ikjun Choi, Ilmun Kim

Recent years have seen a surge in methods for two-sample testing, among which the Maximum Mean Discrepancy (MMD) test has emerged as an effective tool for handling complex and high…

stat.CO2026

More Permutations Do Not Always Increase Power: Non-monotonicity in Monte Carlo Permutation Tests

Suman Cha, Seongchan Lee, Antonin Schrab +1

Monte Carlo permutation tests are a cornerstone of valid, model-free statistical inference. A widely held practical intuition is that increasing the number of sampled permutations…