Pragya Sur

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 13

Top Topics

Invariant Representation

Decision Stumps

Likelihood Ratio Test

Boosting Algorithms

Top Venues

Publications

Yanke Song, Sohom Bhattacharya, Pragya Sur
Generalization error of min-norm interpolators in transfer learning. CoRR (2024)
John C. Duchi, Suyash Gupta, Kuanhao Jiang, Pragya Sur
Predictive Inference in Multi-environment Scenarios. CoRR (2024)
Kevin Luo, Yufan Li, Pragya Sur
ROTI-GCV: Generalized Cross-Validation for right-ROTationally Invariant Data. CoRR (2024)
Yufan Li, Pragya Sur
Spectrum-Aware Adjustment: A New Debiasing Framework with Applications to Principal Components Regression. CoRR (2023)
Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland, Nati Srebro
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models. NeurIPS (2022)
Tengyuan Liang, Subhabrata Sen, Pragya Sur
High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models. CoRR (2022)
Cathy Shyr, Pragya Sur, Giovanni Parmigiani, Prasad Patil
Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensembling. CoRR (2022)
Lijia Zhou, Frederic Koehler, Pragya Sur, Danica J. Sutherland, Nathan Srebro
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models. CoRR (2022)
Tengyuan Liang, Pragya Sur
A Precise High-Dimensional Asymptotic Theory for Boosting and Min-L1-Norm Interpolated Classifiers. CoRR (2020)
Cynthia Dwork, Christina Ilvento, Guy N. Rothblum, Pragya Sur
Abstracting Fairness: Oracles, Metrics, and Interpretability. CoRR (2020)
Cynthia Dwork, Christina Ilvento, Guy N. Rothblum, Pragya Sur
Abstracting Fairness: Oracles, Metrics, and Interpretability. FORC (2020)
Zhun Deng, Frances Ding, Cynthia Dwork, Rachel Hong, Giovanni Parmigiani, Prasad Patil, Pragya Sur
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations. CoRR (2020)
Pragya Sur, Yuxin Chen, Emmanuel J. Candès
The Likelihood Ratio Test in High-Dimensional Logistic Regression Is Asymptotically a Rescaled Chi-Square. CoRR (2017)