3 citations · 5 across the 3 of their papers we have counts for
7 papers
Local permutation tests for conditional independence
Ilmun Kim, Matey Neykov, Sivaraman Balakrishnan +1
In this paper, we investigate local permutation tests for testing conditional independence between two random vectors and given . The local permutation test determines t…
Randomized tests for high-dimensional regression: A more efficient and powerful solution
Yue Li, Ilmun Kim, Yuting Wei
We investigate the problem of testing the global null in the high-dimensional regression models when the feature dimension grows proportionally to the number of observations $n…
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations
Niccolò Dalmasso, Ann B. Lee, Rafael Izbicki +3
Complex phenomena in engineering and the sciences are often modeled with computationally intensive feed-forward simulations for which a tractable analytic likelihood does not exist…
Comparing a Large Number of Multivariate Distributions
Ilmun Kim
In this paper, we propose a test for the equality of multiple distributions based on kernel mean embeddings. Our framework provides a flexible way to handle multivariate or even hi…
Multinomial Goodness-of-Fit Based on U-Statistics: High-Dimensional Asymptotic and Minimax Optimality
Ilmun Kim
We consider multinomial goodness-of-fit tests in the high-dimensional regime where the number of bins increases with the sample size. In this regime, Pearson's chi-squared test can…
Global and Local Two-Sample Tests via Regression
Ilmun Kim, Ann B. Lee, Jing Lei
Two-sample testing is a fundamental problem in statistics. Despite its long history, there has been renewed interest in this problem with the advent of high-dimensional and complex…