Fanny Yang


I am an Assistant Professor in the Computer Science Department (D-INFK) at ETH Zurich. Previously I was a postdoctoral Scholar at Stanford University working with John Duchi and Percy Liang and a Junior Fellow at the Institute for Theoretical Studies at ETH Zurich working with Nicolai Meinshausen. Before that, I was a PhD student at the EECS department of UC Berkeley advised by Martin Wainwright.

Research interests

I’m generally interested in theoretically understanding and developing tools in machine learning and statistics that work well. Currently I am particularly curious about gaining theoretical understanding for the generalization properties of overparameterized models for high-dimensional data (motivated by neural networks), as well as a plethora of questions related to obtaining more trustworthy ML models, specifically distributional robustness, domain generalization and interpretability.

For the latter branch of questions I’m particularly excited about problems in the medical domain - hence if you’re facing concrete reliability issues when using ML for medical diagnostics or treatment, please don’t hesitate to ping me.

Recent talk slides

  • (2022) At MSRI workshop Foundations of Stable, Generalizable and Transferable Statistical Learning on fast rates for interpolation for min-lp-norm interpolation (for p in [1,2]) and issues of interpolating models for robust evaluation slides
  • (2021) At ELLIS Doctoral symposium on limits of rotationally invariant kernels in high dimensions (such as NTK) and semi-supervised novelty detection slides

Recent papers

                                        1. Margin-based sampling in high dimensions: When being active is less efficient than staying passive
                                          Alexandru Tifrea*, Jacob Clarysse*, and Fanny Yang
                                          International Conference on Machine Learning (ICML), 2023
                                        2. Strong inductive biases provably prevent harmless interpolation
                                          Michael Aerni*, Marco Milanta*, Konstantin Donhauser, and Fanny Yang
                                          International Conference on Learning Representations (ICLR), 2023
                                        3. Why adversarial training can hurt robust accuracy
                                          Jacob Clarysse, Julia Hörrmann, and Fanny Yang
                                          International Conference on Learning Representations (ICLR), 2023
                                        1. Tight bounds for maximum l1-margin classifiers
                                          Stefan Stojanovic, Konstantin Donhauser, and Fanny Yang
                                          arXiv preprint, 2022
                                        2. Provable concept learning for interpretable predictions using variational inference
                                          Armeen Taeb, Nicolo Ruggeri, Carina Schnuck, and Fanny Yang
                                          arXiv preprint, 2022
                                        1. How unfair is private learning?
                                          Amartya Sanyal*, Yaxi Hu*, and Fanny Yang
                                          Conference on Uncertainty in Artificial Intelligence (UAI), Oral, 2022
                                        2. Semi-supervised novelty detection using ensembles with regularized disagreement
                                          Alexandru Țifrea, Eric Stavarache, and Fanny Yang
                                          Conference on Uncertainty in Artificial Intelligence (UAI), 2022
                                        3. Fast rates for noisy interpolation require rethinking the effects of inductive bias
                                          Konstantin Donhauser, Nicolo Ruggeri, Stefan Stojanovic, and Fanny Yang
                                          International Conference on Machine Learning (ICML), 2022
                                        4. Tight bounds for minimum l1-norm interpolation of noisy data
                                          Guillaume Wang*, Konstantin Donhauser*, and Fanny Yang
                                          International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
                                          1. Self-supervised Reinforcement Learning with Independently Controllable Subgoals
                                            Andrii Zadaianchuk, Georg Martius, and Fanny Yang
                                            Conference on Robot Learning (CoRL), 2021
                                          2. How rotational invariance of common kernels prevents generalization in high dimensions
                                            Konstantin Donhauser, Mingqi Wu, and Fanny Yang
                                            International Conference on Machine Learning (ICML), 2021
                                          3. Interpolation can hurt robust generalization even when there is no noise
                                            Konstantin Donhauser*, Alexandru Tifrea*, Michael Aerni, Reinhard Heckel, and Fanny Yang
                                            Neural Information Processing Systems (NeurIPS), 2021
                                            1. Understanding and Mitigating the Tradeoff between Robustness and Accuracy
                                              Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John Duchi, and Percy Liang
                                              International Conference on Machine Learning (ICML), 2020
                                              1. Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness
                                                Fanny Yang, Zuowen Wang, and Christina Heinze-Deml
                                                Neural Information Processing Systems (NeurIPS), 2019

                                                      Selected older publications

                                                      1. Early stopping for kernel boosting algorithms: A general analysis with localized complexities
                                                        Fanny Yang*, Yuting Wei*, and Martin J Wainwright
                                                        IEEE Transactions on Information Theory (IEEE IT), 2019
                                                        Neural Information Processing Systems (NeurIPS), Spotlight, 2017
                                                      2. A framework for multi-A(rmed)/B(andit) testing with online fdr control
                                                        Fanny Yang, Aaditya Ramdas, Kevin G Jamieson, and Martin J Wainwright
                                                        Neural Information Processing Systems (NeurIPS), Spotlight, 2017
                                                      3. Statistical and computational guarantees for the Baum-Welch algorithm
                                                        Fanny Yang, Sivaraman Balakrishnan, and Martin J Wainwright
                                                        Journal for Marchine Learning Research (JMLR), 2017
                                                      4. Phase Retrieval via Structured Modulation in Paley-Wiener Spaces
                                                        F Yang, V Pohl, and H Boche
                                                        International Conference on Sampling Theory and Applications 2013

                                                      Short C.V.

                                                      01/2020 - present Assistant Professor, ETH Zurich
                                                      04/2019 - 12/2019 Postdoctoral Fellow, Stanford University
                                                      09/2018 - 09/2019 Junior Fellow (Postdoc), ETH Zurich
                                                      06/2017 - 02/2018 Applied Scientist Intern, Amazon AWS, Palo Alto
                                                      08/2013 - 08/2018 PhD, UC Berkeley
                                                      10/2010 - 08/2013 M. Sc., Technical University Munich (TUM)
                                                      10/2007 - 10/2010 B.Sc., Karlsruhe Institute of Technology (KIT)


                                                      The best way to reach me is via e-mail at fan.yang (at) however note that I cannot respond to most requests although I try to answer all research-related messages.

                                                      Meetings take place in my office: CAB G19.1
                                                      Note: Enter the north side of the CAB building and walk up to G floor
                                                      The G floor is not connected, hence it’d be a pity if you reach it in the wrong section

                                                      Personal information about me can be found on my website