21 citations · 75 across the 24 of their papers we have counts for
31 papers
Partially Performative Prediction
Jaewook Lee, Tijana Zrnic
Performative prediction studies feedback loops that arise when predictive models are deployed in consequential domains. In these settings, deploying a model can change the populati…
Valid Inference with Synthetic Data via Task Exchangeability
Lezhi Tan, Tijana Zrnic
There is a proliferation of work arguing for the use of synthetic data in scientific research. For example, social scientists are arguing for the use of LLM-generated "silicon samp…
Look-Ahead Reasoning on Learning Platforms
Haiqing Zhu, Tijana Zrnic, Celestine Mendler-Dünner
On many learning platforms, the optimization criteria guiding model training reflect the priorities of the designer rather than those of the individuals they affect. Consequently,…
Robust Sampling for Active Statistical Inference
Puheng Li, Tijana Zrnic, Emmanuel Candès
Active statistical inference is a new method for inference with AI-assisted data collection. Given a budget on the number of labeled data points that can be collected and assuming…
Probably Approximately Correct Labels
Emmanuel J. Candès, Andrew Ilyas, Tijana Zrnic
Obtaining high-quality labeled datasets is often costly, requiring either human annotation or expensive experiments. In theory, powerful pre-trained AI models provide an opportunit…
Prediction-Powered Inference with Imputed Covariates and Nonuniform Sampling
Dan M. Kluger, Kerri Lu, Tijana Zrnic +2
Machine learning models are increasingly used to produce predictions that serve as input data in subsequent statistical analyses. For example, computer vision predictions of econom…