34 citations · 169 across the 29 of their papers we have counts for
7 papers · 1 filter
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…
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…
Locally Simultaneous Inference
Tijana Zrnic, William Fithian
Selective inference is the problem of giving valid answers to statistical questions chosen in a data-driven manner. A standard solution to selective inference is simultaneous infer…
Valid Inference After Causal Discovery
Paula Gradu, Tijana Zrnic, Yixin Wang +1
Causal discovery and causal effect estimation are two fundamental tasks in causal inference. While many methods have been developed for each task individually, statistical challeng…
The Power of Batching in Multiple Hypothesis Testing
Tijana Zrnic, Daniel L. Jiang, Aaditya Ramdas +1
One important partition of algorithms for controlling the false discovery rate (FDR) in multiple testing is into offline and online algorithms. The first generally achieve signific…
Asynchronous Online Testing of Multiple Hypotheses
Tijana Zrnic, Aaditya Ramdas, Michael I. Jordan
We consider the problem of asynchronous online testing, aimed at providing control of the false discovery rate (FDR) during a continual stream of data collection and testing, where…
SAFFRON: an adaptive algorithm for online control of the false discovery rate
Aaditya Ramdas, Tijana Zrnic, Martin Wainwright +1
In the online false discovery rate (FDR) problem, one observes a possibly infinite sequence of -values , each testing a different null hypothesis, and an algorith…