Ruth Urner

Affiliations:
  • MPI for Intelligent Systems, Tuebingen, Germany


According to our database1, Ruth Urner authored at least 34 papers between 2010 and 2023.

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Bibliography

2023
Adversarially Robust Learning with Uncertain Perturbation Sets.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Strategic Classification with Unknown User Manipulations.
Proceedings of the International Conference on Machine Learning, 2023

Adversarially Robust Learning with Tolerance.
Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Precision Recall Cover: A Method For Assessing Generative Models.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Robustness Should Not Be at Odds with Accuracy.
Proceedings of the 3rd Symposium on Foundations of Responsible Computing, 2022

Learning Losses for Strategic Classification.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
On the (Un-)Avoidability of Adversarial Examples.
CoRR, 2021

Identifying regions of trusted predictions.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Open Problem: Are all VC-classes CPAC learnable?
Proceedings of the Conference on Learning Theory, 2021

2020
Black-box Certification and Learning under Adversarial Perturbations.
Proceedings of the 37th International Conference on Machine Learning, 2020

On Learnability wih Computable Learners.
Proceedings of the Algorithmic Learning Theory, 2020

2019
When can unlabeled data improve the learning rate?
Proceedings of the Conference on Learning Theory, 2019

2017
Active Nearest-Neighbor Learning in Metric Spaces.
J. Mach. Learn. Res., 2017

2016
Active Learning - Modern Learning Theory.
Encyclopedia of Algorithms, 2016

Foundations of Unsupervised Learning (Dagstuhl Seminar 16382).
Dagstuhl Reports, 2016

Lifelong Learning with Weighted Majority Votes.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

On Version Space Compression.
Proceedings of the Algorithmic Learning Theory - 27th International Conference, 2016

2015
Active Nearest Neighbors in Changing Environments.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Hierarchical Label Queries with Data-Dependent Partitions.
Proceedings of The 28th Conference on Learning Theory, 2015

Efficient Learning of Linear Separators under Bounded Noise.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Domain adaptation-can quantity compensate for quality?
Ann. Math. Artif. Intell., 2014

Learning Economic Parameters from Revealed Preferences.
Proceedings of the Web and Internet Economics - 10th International Conference, 2014

The sample complexity of agnostic learning with deterministic labels.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2014

The sample complexity of agnostic learning under deterministic labels.
Proceedings of The 27th Conference on Learning Theory, 2014

2013
Learning with non-Standard Supervision.
PhD thesis, 2013

Generative Multiple-Instance Learning Models For Quantitative Electromyography.
Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence, 2013

Monochromatic Bi-Clustering.
Proceedings of the 30th International Conference on Machine Learning, 2013

PLAL: Cluster-based active learning.
Proceedings of the COLT 2013, 2013

2012
Learning from Weak Teachers.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Domain Adaptation--Can Quantity compensate for Quality?.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2012

On the Hardness of Domain Adaptation and the Utility of Unlabeled Target Samples.
Proceedings of the Algorithmic Learning Theory - 23rd International Conference, 2012

2011
Access to Unlabeled Data can Speed up Prediction Time.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
On a disparity between relative cliquewidth and relative NLC-width.
Discret. Appl. Math., 2010

Naïve Security in a Wi-Fi World.
Proceedings of the Trust Management IV - 4th IFIP WG 11.11 International Conference, 2010


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