240 citations · 329 across the 12 of their papers we have counts for
12 papers
A Non-Asymptotic Moreau Envelope Theory for High-Dimensional Generalized Linear Models
Lijia Zhou, Frederic Koehler, Pragya Sur +2
We prove a new generalization bound that shows for any class of linear predictors in Gaussian space, the Rademacher complexity of the class and the training error under any continu…
Multi-Study Boosting: Theoretical Considerations for Merging vs. Ensembling
Cathy Shyr, Pragya Sur, Giovanni Parmigiani +1
Cross-study replicability is a powerful model evaluation criterion that emphasizes generalizability of predictions. When training cross-study replicable prediction models, it is cr…
A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond
Kuanhao Jiang, Rajarshi Mukherjee, Subhabrata Sen +1
Estimation of the average treatment effect (ATE) is a central problem in causal inference. In recent times, inference for the ATE in the presence of high-dimensional covariates has…
High-dimensional Asymptotics of Langevin Dynamics in Spiked Matrix Models
Tengyuan Liang, Subhabrata Sen, Pragya Sur
We study Langevin dynamics for recovering the planted signal in the spiked matrix model. We provide a "path-wise" characterization of the overlap between the output of the Langevin…
Representation via Representations: Domain Generalization via Adversarially Learned Invariant Representations
Zhun Deng, Frances Ding, Cynthia Dwork +4
We investigate the power of censoring techniques, first developed for learning {\em fair representations}, to address domain generalization. We examine {\em adversarial} censoring…
Abstracting Fairness: Oracles, Metrics, and Interpretability
Cynthia Dwork, Christina Ilvento, Guy N. Rothblum +1
It is well understood that classification algorithms, for example, for deciding on loan applications, cannot be evaluated for fairness without taking context into account. We exami…