3 papers
math.ST2026
On the optimality of antithetic randomization for cross-validation
Srijan Chattopadhyay, Sifan Liu, Snigdha Panigrahi
In the classical normal means problem, independent train--test folds can be constructed by perturbing the data with normal randomization. Averaging over such folds yields a cro…
stat.ME2025
Flexible Selective Inference with Flow-based Transport Maps
Sifan Liu, Snigdha Panigrahi
Data-carving methods perform selective inference by conditioning the distribution of data on the observed selection event. However, existing data-carving approaches typically requi…
stat.ME2024
Cross-Validation with Antithetic Gaussian Randomization
Sifan Liu, Snigdha Panigrahi, Jake A. Soloff
We introduce a new cross-validation method based on an equicorrelated Gaussian randomization scheme. Our method is well-suited for problems where sample splitting is infeasible, ei…