Fanny Yang

According to our database, Fanny Yang authored at least 43 papers between 2012 and 2024.

Collaborative distances:

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

2024

Atmospheric Transport Modeling of CO₂ with Neural Networks.

Vitus Benson, Ana Bastos, Christian Reimers, Alexander J. Winkler, Fanny Yang, Markus Reichstein

CoRR, 2024

Strong Copyright Protection for Language Models via Adaptive Model Fusion.

Javier Abad, Konstantin Donhauser, Francesco Pinto, Fanny Yang

CoRR, 2024

Robust Mixture Learning when Outliers Overwhelm Small Groups.

Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang

CoRR, 2024

Detecting critical treatment effect bias in small subgroups.

Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang

CoRR, 2024

PILLAR: How to make semi-private learning more effective.

Francesco Pinto, Yaxi Hu, Fanny Yang, Amartya Sanyal

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

Minimum Norm Interpolation Meets The Local Theory of Banach Spaces.

Gil Kur, Pedro Abdalla, Pierre Bizeul, Fanny Yang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent.

Konstantin Donhauser, Javier Abad Martinez, Neha Hulkund, Fanny Yang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tight bounds for maximum ℓ₁-margin classifiers.

Stefan Stojanovic, Konstantin Donhauser, Fanny Yang

Proceedings of the International Conference on Algorithmic Learning Theory, 2024

Certified private data release for sparse Lipschitz functions.

Konstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

Hidden yet quantifiable: A lower bound for confounding strength using randomized trials.

Piersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser, Fanny Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

How robust accuracy suffers from certified training with convex relaxations.

Piersilvio De Bartolomeis, Jacob Clarysse, Amartya Sanyal, Fanny Yang

CoRR, 2023

Sample-efficient private data release for Lipschitz functions under sparsity assumptions.

Konstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang

CoRR, 2023

Can semi-supervised learning use all the data effectively? A lower bound perspective.

Alexandru Tifrea, Gizem Yüce, Amartya Sanyal, Fanny Yang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Alexandru Tifrea, Jacob Clarysse, Fanny Yang

Proceedings of the International Conference on Machine Learning, 2023

Why adversarial training can hurt robust accuracy.

Jacob Clarysse, Julia Hörrmann, Fanny Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Strong inductive biases provably prevent harmless interpolation.

Michael Aerni, Marco Milanta, Konstantin Donhauser, Fanny Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

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

Alexandru Tifrea, Jacob Clarysse, Fanny Yang

CoRR, 2022

Provable concept learning for interpretable predictions using variational inference.

Armeen Taeb, Nicolò Ruggeri, Carina Schnuck, Fanny Yang

CoRR, 2022

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

Konstantin Donhauser, Nicolò Ruggeri, Stefan Stojanovic, Fanny Yang

CoRR, 2022

Semi-supervised novelty detection using ensembles with regularized disagreement.

Alexandru Tifrea, Eric Stavarache, Fanny Yang

Proceedings of the Uncertainty in Artificial Intelligence, 2022

How unfair is private learning?

Amartya Sanyal, Yaxi Hu, Fanny Yang

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Fast rates for noisy interpolation require rethinking the effect of inductive bias.

Konstantin Donhauser, Nicolò Ruggeri, Stefan Stojanovic, Fanny Yang

Proceedings of the International Conference on Machine Learning, 2022

Tight bounds for minimum ℓ₁-norm interpolation of noisy data.

Guillaume Wang, Konstantin Donhauser, Fanny Yang

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Tight bounds for minimum l1-norm interpolation of noisy data.

Guillaume Wang, Konstantin Donhauser, Fanny Yang

CoRR, 2021

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

Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Novel Disease Detection Using Ensembles with Regularized Disagreement.

Alexandru Tifrea, Eric Stavarache, Fanny Yang

Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis, 2021

How rotational invariance of common kernels prevents generalization in high dimensions.

Konstantin Donhauser, Mingqi Wu, Fanny Yang

Proceedings of the 38th International Conference on Machine Learning, 2021

Self-supervised Reinforcement Learning with Independently Controllable Subgoals.

Andrii Zadaianchuk, Georg Martius, Fanny Yang

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

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

Alexandru Tifrea, Eric Stavarache, Fanny Yang

CoRR, 2020

Understanding and Mitigating the Tradeoff between Robustness and Accuracy.

Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

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

Yuting Wei, Fanny Yang, Martin J. Wainwright

IEEE Trans. Inf. Theory, 2019

Adversarial Training Can Hurt Generalization.

Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang

CoRR, 2019

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

Fanny Yang, Zuowen Wang, Christina Heinze-Deml

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Regularized Learning for Domain Adaptation under Label Shifts.

Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Statistics meets Optimization: Computational guarantees for statistical learning algorithms.

Fanny Yang

PhD thesis, 2018

2017

Statistical and Computational Guarantees for the Baum-Welch Algorithm.

Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright

J. Mach. Learn. Res., 2017

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

Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson, Martin J. Wainwright

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Online control of the false discovery rate with decaying memory.

Aaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I. Jordan

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2014

A phase retrieval method for signals in modulation-invariant spaces.

Volker Pohl, Çagkan Yapar, Holger Boche, Fanny Yang

Proceedings of the IEEE International Conference on Acoustics, 2014

2013

Phaseless Signal Recovery in Infinite Dimensional Spaces using Structured Modulations

Volker Pohl, Fanny Yang, Holger Boche

CoRR, 2013

Phase Retrieval via Structured Modulations in Paley-Wiener Spaces

Fanny Yang, Volker Pohl, Holger Boche

CoRR, 2013

Phase retrieval from low rate samples.

Volker Pohl, Fanny Yang, Holger Boche

CoRR, 2013

2012

Causal reconstruction kernels for consistent signal recovery.

Volker Pohl, Fanny Yang, Holger Boche

Proceedings of the 20th European Signal Processing Conference, 2012