40 citations · 113 across the 12 of their papers we have counts for
5 papers · 1 filter
Optimal Inference with Black-box Predictions
Lucas Kania, Abhinav Chakraborty, Edward Kennedy +2
Powerful black-box predictive models have motivated many proposals for combining observed data with predictions to perform valid statistical inference. Despite this progress, the f…
Semi-Supervised U-statistics
Ilmun Kim, Larry Wasserman, Sivaraman Balakrishnan +1
Semi-supervised datasets are ubiquitous across diverse domains where obtaining fully labeled data is costly or time-consuming. The prevalence of such datasets has consistently driv…
Nearly Minimax Optimal Wasserstein Conditional Independence Testing
Matey Neykov, Larry Wasserman, Ilmun Kim +1
This paper is concerned with minimax conditional independence testing. In contrast to some previous works on the topic, which use the total variation distance to separate the null…
Conditional Independence Testing for Discrete Distributions: Beyond - and -tests
Ilmun Kim, Matey Neykov, Sivaraman Balakrishnan +1
This paper is concerned with the problem of conditional independence testing for discrete data. In recent years, researchers have shed new light on this fundamental problem, emphas…
Statistical guarantees for the EM algorithm: From population to sample-based analysis
Sivaraman Balakrishnan, Martin J. Wainwright, Bin Yu
We develop a general framework for proving rigorous guarantees on the performance of the EM algorithm and a variant known as gradient EM. Our analysis is divided into two parts: a…