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Books and Theses
- 2018
[b1]Fanny Yang:
Statistics meets Optimization: Computational guarantees for statistical learning algorithms. University of California, Berkeley, USA, 2018
Journal Articles
- 2019
- [j2]Yuting Wei
, Fanny Yang, Martin J. Wainwright:
Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities. IEEE Trans. Inf. Theory 65(10): 6685-6703 (2019) - 2017
- [j1]Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright:
Statistical and Computational Guarantees for the Baum-Welch Algorithm. J. Mach. Learn. Res. 18: 125:1-125:53 (2017)
Conference and Workshop Papers
- 2024
- [c27]Piersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser, Fanny Yang:
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials. AISTATS 2024: 1045-1053 - [c26]Konstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang:
Certified private data release for sparse Lipschitz functions. AISTATS 2024: 1396-1404 - [c25]Stefan Stojanovic, Konstantin Donhauser, Fanny Yang:
Tight bounds for maximum ℓ1-margin classifiers. ALT 2024: 1055-1112 - [c24]Konstantin Donhauser, Javier Abad Martinez, Neha Hulkund, Fanny Yang:
Privacy-Preserving Data Release Leveraging Optimal Transport and Particle Gradient Descent. ICML 2024 - [c23]Gil Kur, Pedro Abdalla, Pierre Bizeul, Fanny Yang:
Minimum Norm Interpolation Meets The Local Theory of Banach Spaces. ICML 2024 - [c22]Francesco Pinto, Yaxi Hu, Fanny Yang, Amartya Sanyal:
PILLAR: How to make semi-private learning more effective. SaTML 2024: 110-139 - 2023
- [c21]Michael Aerni, Marco Milanta, Konstantin Donhauser, Fanny Yang:
Strong inductive biases provably prevent harmless interpolation. ICLR 2023 - [c20]Jacob Clarysse, Julia Hörrmann, Fanny Yang:
Why adversarial training can hurt robust accuracy. ICLR 2023 - [c19]Alexandru Tifrea, Jacob Clarysse, Fanny Yang:
Margin-based sampling in high dimensions: When being active is less efficient than staying passive. ICML 2023: 34222-34262 - [c18]Alexandru Tifrea, Gizem Yüce, Amartya Sanyal, Fanny Yang:
Can semi-supervised learning use all the data effectively? A lower bound perspective. NeurIPS 2023 - 2022
- [c17]Guillaume Wang, Konstantin Donhauser, Fanny Yang:
Tight bounds for minimum ℓ1-norm interpolation of noisy data. AISTATS 2022: 10572-10602 - [c16]Konstantin Donhauser, Nicolò Ruggeri, Stefan Stojanovic, Fanny Yang:
Fast rates for noisy interpolation require rethinking the effect of inductive bias. ICML 2022: 5397-5428 - [c15]Amartya Sanyal, Yaxi Hu, Fanny Yang:
How unfair is private learning? UAI 2022: 1738-1748 - [c14]Alexandru Tifrea, Eric Stavarache, Fanny Yang:
Semi-supervised novelty detection using ensembles with regularized disagreement. UAI 2022: 1939-1948 - 2021
- [c13]Andrii Zadaianchuk, Georg Martius, Fanny Yang:
Self-supervised Reinforcement Learning with Independently Controllable Subgoals. CoRL 2021: 384-394 - [c12]Konstantin Donhauser, Mingqi Wu, Fanny Yang:
How rotational invariance of common kernels prevents generalization in high dimensions. ICML 2021: 2804-2814 - [c11]Alexandru Tifrea, Eric Stavarache, Fanny Yang:
Novel Disease Detection Using Ensembles with Regularized Disagreement. UNSURE/PIPPI@MICCAI 2021: 133-144 - [c10]Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang:
Interpolation can hurt robust generalization even when there is no noise. NeurIPS 2021: 23465-23477 - 2020
- [c9]Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang:
Understanding and Mitigating the Tradeoff between Robustness and Accuracy. ICML 2020: 7909-7919 - 2019
- [c8]Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar:
Regularized Learning for Domain Adaptation under Label Shifts. ICLR (Poster) 2019 - [c7]Fanny Yang, Zuowen Wang, Christina Heinze-Deml:
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness. NeurIPS 2019: 14757-14768 - 2017
- [c6]Aaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I. Jordan:
Online control of the false discovery rate with decaying memory. NIPS 2017: 5650-5659 - [c5]Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson, Martin J. Wainwright:
A framework for Multi-A(rmed)/B(andit) Testing with Online FDR Control. NIPS 2017: 5957-5966 - [c4]Yuting Wei, Fanny Yang, Martin J. Wainwright:
Early stopping for kernel boosting algorithms: A general analysis with localized complexities. NIPS 2017: 6065-6075 - 2015
- [c3]Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright:
Statistical and computational guarantees for the Baum-Welch algorithm. Allerton 2015: 658-665 - 2014
- [c2]Volker Pohl, Çagkan Yapar, Holger Boche, Fanny Yang:
A phase retrieval method for signals in modulation-invariant spaces. ICASSP 2014: 46-50 - 2012
- [c1]Volker Pohl, Fanny Yang, Holger Boche:
Causal reconstruction kernels for consistent signal recovery. EUSIPCO 2012: 1174-1178
Informal and Other Publications
- 2024
- [i33]Konstantin Donhauser, Javier Abad Martinez, Neha Hulkund, Fanny Yang:
Privacy-preserving data release leveraging optimal transport and particle gradient descent. CoRR abs/2401.17823 (2024) - [i32]Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang:
Detecting critical treatment effect bias in small subgroups. CoRR abs/2404.18905 (2024) - [i31]Daniil Dmitriev, Rares-Darius Buhai, Stefan Tiegel, Alexander Wolters, Gleb Novikov, Amartya Sanyal, David Steurer, Fanny Yang:
Robust Mixture Learning when Outliers Overwhelm Small Groups. CoRR abs/2407.15792 (2024) - [i30]Javier Abad, Konstantin Donhauser, Francesco Pinto, Fanny Yang:
Strong Copyright Protection for Language Models via Adaptive Model Fusion. CoRR abs/2407.20105 (2024) - [i29]Vitus Benson, Ana Bastos, Christian Reimers, Alexander J. Winkler, Fanny Yang, Markus Reichstein:
Atmospheric Transport Modeling of CO2 with Neural Networks. CoRR abs/2408.11032 (2024) - 2023
- [i28]Michael Aerni, Marco Milanta, Konstantin Donhauser, Fanny Yang:
Strong inductive biases provably prevent harmless interpolation. CoRR abs/2301.07605 (2023) - [i27]Konstantin Donhauser, Johan Lokna, Amartya Sanyal, March Boedihardjo, Robert Hönig, Fanny Yang:
Sample-efficient private data release for Lipschitz functions under sparsity assumptions. CoRR abs/2302.09680 (2023) - [i26]Francesco Pinto, Yaxi Hu, Fanny Yang, Amartya Sanyal:
PILLAR: How to make semi-private learning more effective. CoRR abs/2306.03962 (2023) - [i25]Piersilvio De Bartolomeis, Jacob Clarysse, Amartya Sanyal, Fanny Yang:
How robust accuracy suffers from certified training with convex relaxations. CoRR abs/2306.06995 (2023) - [i24]Alexandru Tifrea, Gizem Yüce, Amartya Sanyal, Fanny Yang:
Can semi-supervised learning use all the data effectively? A lower bound perspective. CoRR abs/2311.18557 (2023) - [i23]Piersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser, Fanny Yang:
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials. CoRR abs/2312.03871 (2023) - 2022
- [i22]Jacob Clarysse, Julia Hörrmann, Fanny Yang:
Why adversarial training can hurt robust accuracy. CoRR abs/2203.02006 (2022) - [i21]Konstantin Donhauser, Nicolò Ruggeri, Stefan Stojanovic, Fanny Yang:
Fast rates for noisy interpolation require rethinking the effects of inductive bias. CoRR abs/2203.03597 (2022) - [i20]Armeen Taeb, Nicolò Ruggeri, Carina Schnuck, Fanny Yang:
Provable concept learning for interpretable predictions using variational inference. CoRR abs/2204.00492 (2022) - [i19]Amartya Sanyal, Yaxi Hu, Fanny Yang:
How unfair is private learning ? CoRR abs/2206.03985 (2022) - [i18]Alexandru Tifrea, Jacob Clarysse, Fanny Yang:
Uniform versus uncertainty sampling: When being active is less efficient than staying passive. CoRR abs/2212.00772 (2022) - [i17]Stefan Stojanovic, Konstantin Donhauser, Fanny Yang:
Tight bounds for maximum 𝓁1-margin classifiers. CoRR abs/2212.03783 (2022) - 2021
- [i16]Konstantin Donhauser, Mingqi Wu, Fanny Yang:
How rotational invariance of common kernels prevents generalization in high dimensions. CoRR abs/2104.04244 (2021) - [i15]Konstantin Donhauser, Alexandru Tifrea, Michael Aerni, Reinhard Heckel, Fanny Yang:
Interpolation can hurt robust generalization even when there is no noise. CoRR abs/2108.02883 (2021) - [i14]Andrii Zadaianchuk, Georg Martius, Fanny Yang:
Self-supervised Reinforcement Learning with Independently Controllable Subgoals. CoRR abs/2109.04150 (2021) - [i13]Guillaume Wang, Konstantin Donhauser, Fanny Yang:
Tight bounds for minimum l1-norm interpolation of noisy data. CoRR abs/2111.05987 (2021) - 2020
- [i12]Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang:
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy. CoRR abs/2002.10716 (2020) - [i11]Alexandru Tifrea, Eric Stavarache, Fanny Yang:
Learn what you can't learn: Regularized Ensembles for Transductive Out-of-distribution Detection. CoRR abs/2012.05825 (2020) - 2019
- [i10]Kamyar Azizzadenesheli, Anqi Liu, Fanny Yang, Animashree Anandkumar:
Regularized Learning for Domain Adaptation under Label Shifts. CoRR abs/1903.09734 (2019) - [i9]Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang:
Adversarial Training Can Hurt Generalization. CoRR abs/1906.06032 (2019) - [i8]Fanny Yang, Zuowen Wang, Christina Heinze-Deml:
Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness. CoRR abs/1906.11235 (2019) - 2017
- [i7]Fanny Yang, Aaditya Ramdas, Kevin G. Jamieson, Martin J. Wainwright:
A framework for Multi-A(rmed)/B(andit) testing with online FDR control. CoRR abs/1706.05378 (2017) - [i6]Yuting Wei, Fanny Yang, Martin J. Wainwright:
Early stopping for kernel boosting algorithms: A general analysis with localized complexities. CoRR abs/1707.01543 (2017) - [i5]Aaditya Ramdas, Fanny Yang, Martin J. Wainwright, Michael I. Jordan:
Online control of the false discovery rate with decaying memory. CoRR abs/1710.00499 (2017) - 2015
- [i4]Fanny Yang, Sivaraman Balakrishnan, Martin J. Wainwright:
Statistical and Computational Guarantees for the Baum-Welch Algorithm. CoRR abs/1512.08269 (2015) - 2013
- [i3]Fanny Yang, Volker Pohl, Holger Boche:
Phase Retrieval via Structured Modulations in Paley-Wiener Spaces. CoRR abs/1302.4258 (2013) - [i2]Volker Pohl, Fanny Yang, Holger Boche:
Phaseless Signal Recovery in Infinite Dimensional Spaces using Structured Modulations. CoRR abs/1305.2789 (2013) - [i1]Volker Pohl, Fanny Yang, Holger Boche:
Phase retrieval from low rate samples. CoRR abs/1311.7045 (2013)
Coauthor Index
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