18 citations · 31 across the 14 of their papers we have counts for
5 papers · 1 filter
Large-scale linear hypothesis testing for high-dimensional online M-estimation
Daeyoung Ham, Myeonghun Yu, Tate Jacobson
With the growing prevalence of streaming data, renewable estimation has become an important tool for updating statistical analyses without retaining historical raw observations. We…
Human-AI-Powered Hypothesis Testing: Cost-Aware Selective AI Scoring and Sequential Human Escalation
Dae Woong Ham, Dae Woong, Ham +3
Large language models are increasingly used as inexpensive judges to evaluate outputs, label data, and assess whether a system meets a desired quality standard. Yet using AI judgme…
Debiased inference for proximal dose-response function
Daeyoung Ham, Sihan Wu, Yifan Cui
We study nonparametric inference for a continuous-treatment causal dose-response curve and its first derivative under unmeasured confounding, using treatment- and outcome-inducing…
A General Framework for Optimal Group Sequential Testing via Mixed-Integer Linear Programming
Dae Woong Ham, Stefanus Jasin, Xuejun Zhao
Sequential hypothesis tests are widely adopted as a principled way to perform multiple tests on data that arrives over time. In particular, researchers frequently utilize group seq…
Benefits and Costs of Adaptive Sampling
Yu-Shiou Willy Lin, Dae Woong Ham, Iavor Bojinov
Multi-armed bandits are widely used for sequential experimentation in clinical trials, recommendation systems, and online platforms. While regret minimization and valid inference f…