Pragya Sur

According to our database, Pragya Sur authored at least 13 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling.

Yufan Li, Pragya Sur

CoRR, February, 2025

ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant Data.

Kevin Luo, Yufan Li, Pragya Sur

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Universality in Block Dependent Linear Models With Applications to Nonlinear Regression.

Samriddha Lahiry, Pragya Sur

IEEE Trans. Inf. Theory, December, 2024

Generalization error of min-norm interpolators in transfer learning.

Yanke Song, Sohom Bhattacharya, Pragya Sur

CoRR, 2024

Predictive Inference in Multi-environment Scenarios.

John C. Duchi, Suyash Gupta, Kuanhao Jiang, Pragya Sur

CoRR, 2024

2023

Spectrum-Aware Adjustment: A New Debiasing Framework with Applications to Principal Components Regression.

Yufan Li, Pragya Sur

CoRR, 2023

2022

Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensembling.

Cathy Shyr, Pragya Sur, Giovanni Parmigiani, Prasad Patil

CoRR, 2022

High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models.

Tengyuan Liang, Subhabrata Sen, Pragya Sur

CoRR, 2022

A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models.

Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland, Nati Srebro

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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 Precise High-Dimensional Asymptotic Theory for Boosting and Min-L1-Norm Interpolated Classifiers.

Tengyuan Liang, Pragya Sur

CoRR, 2020

Abstracting Fairness: Oracles, Metrics, and Interpretability.

Cynthia Dwork, Christina Ilvento, Guy N. Rothblum, Pragya Sur

Proceedings of the 1st Symposium on Foundations of Responsible Computing, 2020

2017

The Likelihood Ratio Test in High-Dimensional Logistic Regression Is Asymptotically a Rescaled Chi-Square.

Pragya Sur, Yuxin Chen, Emmanuel J. Candès

CoRR, 2017