The Likelihood Ratio Test in High-Dimensional Logistic Regression Is Asymptotically a Rescaled Chi-Square. - Pragya Sur; Yuxin Chen 002; Emmanuel J. Candès (CoRR, 2017)

Abstracting Fairness: Oracles, Metrics, and Interpretability. - Cynthia Dwork; Christina Ilvento; Guy N. Rothblum; Pragya Sur (FORC, 2020)

A Precise High-Dimensional Asymptotic Theory for Boosting and Min-L1-Norm Interpolated Classifiers. - Tengyuan Liang; Pragya Sur (CoRR, 2020)

Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations. - Zhun Deng; Frances Ding; Cynthia Dwork; Rachel Hong; Giovanni Parmigiani; Prasad Patil; Pragya Sur (CoRR, 2020)

A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models. - Lijia Zhou; Frederic Koehler; Pragya Sur; Danica J. Sutherland; Nati Srebro (NeurIPS, 2022)

High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models. - Tengyuan Liang; Subhabrata Sen; Pragya Sur (CoRR, 2022)

Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensembling. - Cathy Shyr; Pragya Sur; Giovanni Parmigiani; Prasad Patil (CoRR, 2022)

Spectrum-Aware Adjustment: A New Debiasing Framework with Applications to Principal Components Regression. - Yufan Li; Pragya Sur (CoRR, 2023)

Predictive Inference in Multi-environment Scenarios. - John C. Duchi; Suyash Gupta 002; Kuanhao Jiang; Pragya Sur (CoRR, 2024)

Generalization error of min-norm interpolators in transfer learning. - Yanke Song; Sohom Bhattacharya; Pragya Sur (CoRR, 2024)

Universality in Block Dependent Linear Models With Applications to Nonlinear Regression. - Samriddha Lahiry; Pragya Sur (IEEE Trans. Inf. Theory, 2024)

ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant Data. - Kevin Luo; Yufan Li; Pragya Sur (AISTATS, 2025)

Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling. - Yufan Li; Pragya Sur (CoRR, 2025)