7 papers
A Two-Sample Test on Weighted Persistence Intensity Functions in Topological Data Analysis
Yeongung Han, Ilmun Kim, Jisu Kim
The intensity function, defined as the Lebesgue density of the expected measure of a persistence diagram, is a fundamental summary of the probability distribution of persistence di…
When Do Generalized Permutation Tests Achieve Optimal Power? A Dispersion Characterization
Yongmin Kim, Ilmun Kim
We study generalized Monte Carlo permutation tests under a non-uniform distribution on permutations. Focusing on the difference-in-means statistic, we introduce two scalar dispersi…
A Semi-Supervised Kernel Two-Sample Test
Gyumin Lee, Shubhanshu Shekhar, Ilmun Kim
We consider the problem of two-sample testing in a semi-supervised setting with abundant unlabeled covariate data. Standard two-sample tests neglect covariate information, which ha…
Multi-LLM Adaptive Conformal Inference for Reliable LLM Responses
Kangjun Noh, Seongchan Lee, Ilmun Kim +1
Ensuring factuality is essential for the safe use of Large Language Models (LLMs) in high-stakes domains such as medicine and law. Conformal inference provides distribution-free gu…
Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
Yeichan Kim, Ilmun Kim, Seyoung Park
Transfer learning is a key component of modern machine learning, enhancing the performance of target tasks by leveraging diverse data sources. Simultaneously, overparameterized mod…
Locally minimax optimal confidence sets for the best model
Ilmun Kim, Aaditya Ramdas
This paper tackles a fundamental inference problem: given observations from a distribution over with unknown mean , we must form a confidence…