Fanny Yang

发表

Online control of the false discovery rate with decaying memory

Martin J. Wainwright, Michael I. Jordan, Fanny Yang, 2017, NIPS.

Regularized Learning for Domain Adaptation under Label Shifts pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Fanny Yang, 2019, ICLR.

Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities

Martin J. Wainwright, Fanny Yang, Yuting Wei, 2017, IEEE Transactions on Information Theory.

Phase retrieval from low rate samples pdf

Holger Boche, Volker Pohl, Fanny Yang, 2013, ArXiv.

Learn what you can't learn: Regularized Ensembles for Transductive Out-of-distribution Detection pdf

Fanny Yang, Alexandru Tifrea, Eric Stavarache, 2020, ArXiv.

Phase Retrieval via Structured Modulations in Paley-Wiener Spaces pdf

Holger Boche, Volker Pohl, Fanny Yang, 2013, ArXiv.

When Covariate-shifted Data Augmentation Increases Test Error And How to Fix It

John C. Duchi, Sang Michael Xie, Percy Liang, 2019 .

Regularized Learning for Domain Adaptation under Label Shifts pdf

Kamyar Azizzadenesheli, Anima Anandkumar, Anqi Liu, 2019, ICLR.

How unfair is private learning ?

Fanny Yang, Amartya Sanyal, Yaxian Hu, 2022, UAI.

Tight bounds for maximum $\ell_1$-margin classifiers

Fanny Yang, Stefan Stojanovic, Konstantin Donhauser, 2022, 2212.03783.

How unfair is private learning? (Supplementary material)

Fanny Yang, Amartya Sanyal, Yaxian Hu, 2022 .

Uniform versus uncertainty sampling: When being active is less efficient than staying passive

Fanny Yang, A. Tifrea, Jacob Clarysse, 2022, ArXiv.

Phaseless Signal Recovery in Infinite Dimensional Spaces Using Structured Modulations

Fanny Yang, H. Boche, V. Pohl, 2014, Journal of Fourier Analysis and Applications.

Fast rates for noisy interpolation require rethinking the effects of inductive bias

Fanny Yang, Stefan Stojanovic, Konstantin Donhauser, 2022, ICML.

Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness

Fanny Yang, Zuowen Wang, Christina Heinze-Deml, 2019, NeurIPS.

A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control

Martin J. Wainwright, Kevin G. Jamieson, Fanny Yang, 2017, NIPS.

Self-supervised Reinforcement Learning with Independently Controllable Subgoals

Fanny Yang, Georg Martius, Andrii Zadaianchuk, 2021, CoRL.

Tight bounds for minimum l1-norm interpolation of noisy data

Fanny Yang, Konstantin Donhauser, Guillaume Wang, 2021, ArXiv.

Adversarial Training Can Hurt Generalization pdf

Aditi Raghunathan, Percy Liang, John C. Duchi, 2019, ArXiv.

How rotational invariance of common kernels prevents generalization in high dimensions

Mingqi Wu, Fanny Yang, Konstantin Donhauser, 2021, ICML.

Understanding and Mitigating the Tradeoff Between Robustness and Accuracy pdf

John Duchi, Aditi Raghunathan, Percy Liang, 2020, ICML.

Interpolation can hurt robust generalization even when there is no noise pdf

Reinhard Heckel, Fanny Yang, Konstantin Donhauser, 2021, NeurIPS.

Maximizing the robust margin provably overfits on noiseless data

Fanny Yang, Reinhard Heckel, Konstantin Donhauser, 2021 .

How unfair is private learning ?

Fanny Yang, Amartya Sanyal, Yaxian Hu, 2022, UAI.

Novelty detection using ensembles with regularized disagreement

Fanny Yang, ifrea, T. Alexandru, 2021 .

Phaseless Signal Recovery in Infinite Dimensional Spaces Using Structured Modulations

Holger Boche, Volker Pohl, Fanny Yang, 2013, ArXiv.

Provable concept learning for interpretable predictions using variational inference

Fanny Yang, A. Taeb, Nicolò Ruggeri, 2022, ArXiv.

PILLAR: How to make semi-private learning more effective

Fanny Yang, Amartya Sanyal, Yaxian Hu, 2023, ArXiv.

Margin-based sampling in high dimensions: When being active is less efficient than staying passive

Fanny Yang, A. Tifrea, Jacob Clarysse, 2022, ICML.

Tight bounds for maximum $\ell_1$-margin classifiers

Fanny Yang, Stefan Stojanovic, Konstantin Donhauser, 2022, 2212.03783.

How robust accuracy suffers from certified training with convex relaxations

Fanny Yang, Amartya Sanyal, Piersilvio De Bartolomeis, 2023, ArXiv.

Certified defences can hurt generalisation

Fanny Yang, Amartya Sanyal, Piersilvio De Bartolomeis, 2022 .

Statistical and computational guarantees for the Baum-Welch algorithm

Martin J. Wainwright, Sivaraman Balakrishnan, Fanny Yang, 2015, 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton).

Provable concept learning for interpretable predictions using variational autoencoders

Fanny Yang, Nicolò Ruggeri, Carina Schnuck, 2022, 2204.00492.

Semi-supervised novelty detection using ensembles with regularized disagreement

Fanny Yang, A. Tifrea, E. Stavarache, 2020, UAI.

Certified private data release for sparse Lipschitz functions

Fanny Yang, Amartya Sanyal, M. Boedihardjo, 2023, 2302.09680.

Strong inductive biases provably prevent harmless interpolation

Fanny Yang, Marco Milanta, Konstantin Donhauser, 2023, ICLR.