6 papers
Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
Hongyu Chen, David Simchi-Levi, Ruoxuan Xiong
Estimating population quantities such as mean outcomes from user feedback is fundamental to platform evaluation and social science, yet feedback is often missing not at random (MNA…
Designing Service Systems from Textual Evidence
Ruicheng Ao, Hongyu Chen, Siyang Gao +2
Designing service systems requires selecting among alternative configurations -- choosing the best chatbot variant, the optimal routing policy, or the most effective quality contro…
Best Arm Identification with LLM Judges and Limited Human
Ruicheng Ao, Hongyu Chen, Siyang Gao +2
We study fixed-confidence best-arm identification (BAI) where a cheap but potentially biased proxy (e.g., LLM judge) is available for every sample, while an expensive ground-truth…
PPI-SVRG: Unifying Prediction-Powered Inference and Variance Reduction for Semi-Supervised Optimization
Ruicheng Ao, Hongyu Chen, Haoyang Liu +2
We study semi-supervised stochastic optimization when labeled data is scarce but predictions from pre-trained models are available. PPI and SVRG both reduce variance through contro…
Online Resource Allocation with Average Budget Constraints
Ruicheng Ao, Hongyu Chen, David Simchi-Levi +1
We consider the problem of online resource allocation with average budget constraints. At each time point the decision maker makes an irrevocable decision of whether to accept or r…
Prediction-Guided Active Experiments
Ruicheng Ao, Hongyu Chen, David Simchi-Levi
In this work, we introduce a new framework for active experimentation, the Prediction-Guided Active Experiment (PGAE), which leverages predictions from an existing machine learning…