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ORCIDRuth Urner
Person information
- affiliation (since 2017): York University, Lassonde School of Engineering, Department of Electrical Engineering and Computer Science, Toronto, Canada
- affiliation: MPI for Intelligent Systems, Tuebingen, Germany
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2020 – today
- 2025
[c33]Sajad Ashkezari, Ruth Urner:
Refining the Sample Complexity of Comparative Learning. ALT 2025: 67-88- [c32]Hassan Ashtiani, Vinayak Pathak, Ruth Urner:
Simplifying Adversarially Robust PAC Learning With Tolerance. COLT 2025: 147-168 - [i14]Pascale Gourdeau, Tosca Lechner, Ruth Urner:
On the Computability of Multiclass PAC Learning. CoRR abs/2502.06089 (2025) - [i13]Hassan Ashtiani, Vinayak Pathak, Ruth Urner:
Simplifying Adversarially Robust PAC Learning with Tolerance. CoRR abs/2502.07232 (2025) - 2024
- [c31]Pascale Gourdeau, Tosca Lechner, Ruth Urner:
On the Computability of Robust PAC Learning. COLT 2024: 2092-2121 - [c30]Chester Wyke, Ruth Urner
:
An Axiomatic Perspective on Anomaly Detection. ECAI 2024: 3104-3111 - [c29]Alireza Torabian, Ruth Urner:
Investigating Calibrated Classification Scores Through the Lens of Interpretability. xAI (3) 2024: 207-231 - [i12]Pascale Gourdeau, Tosca Lechner, Ruth Urner:
On the Computability of Robust PAC Learning. CoRR abs/2406.10161 (2024) - [i11]Alireza Torabian, Ruth Urner:
Calibration through the Lens of Interpretability. CoRR abs/2412.00943 (2024) - 2023
- [c28]Fasil Cheema, Ruth Urner:
Precision Recall Cover: A Method For Assessing Generative Models. AISTATS 2023: 6571-6594 - [c27]Hassan Ashtiani, Vinayak Pathak, Ruth Urner:
Adversarially Robust Learning with Tolerance. ALT 2023: 115-135 - [c26]Tosca Lechner, Ruth Urner, Shai Ben-David:
Strategic Classification with Unknown User Manipulations. ICML 2023: 18714-18732 - [c25]Tosca Lechner, Vinayak Pathak, Ruth Urner:
Adversarially Robust Learning with Uncertain Perturbation Sets. NeurIPS 2023 - 2022
- [c24]Tosca Lechner, Ruth Urner:
Learning Losses for Strategic Classification. AAAI 2022: 7337-7344 - [c23]Sadia Chowdhury, Ruth Urner:
Robustness Should Not Be at Odds with Accuracy. FORC 2022: 5:1-5:20 - [i10]Hassan Ashtiani, Vinayak Pathak, Ruth Urner:
Adversarially Robust Learning with Tolerance. CoRR abs/2203.00849 (2022) - [i9]Tosca Lechner, Ruth Urner:
Learning Losses for Strategic Classification. CoRR abs/2203.13421 (2022) - 2021
- [c22]Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner:
Open Problem: Are all VC-classes CPAC learnable? COLT 2021: 4636-4641 - [c21]Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner:
Identifying regions of trusted predictions. UAI 2021: 2125-2134 - [i8]Sadia Chowdhury, Ruth Urner:
On the (Un-)Avoidability of Adversarial Examples. CoRR abs/2106.13326 (2021) - 2020
- [c20]Sushant Agarwal, Nivasini Ananthakrishnan, Shai Ben-David, Tosca Lechner, Ruth Urner:
On Learnability wih Computable Learners. ALT 2020: 48-60 - [c19]Hassan Ashtiani, Vinayak Pathak, Ruth Urner:
Black-box Certification and Learning under Adversarial Perturbations. ICML 2020: 388-398 - [i7]Hassan Ashtiani, Vinayak Pathak, Ruth Urner:
Black-box Certification and Learning under Adversarial Perturbations. CoRR abs/2006.16520 (2020)
2010 – 2019
- 2019
- [c18]Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner:
When can unlabeled data improve the learning rate? COLT 2019: 1500-1518 - [i6]Christina Göpfert, Shai Ben-David, Olivier Bousquet, Sylvain Gelly, Ilya O. Tolstikhin, Ruth Urner:
When can unlabeled data improve the learning rate? CoRR abs/1905.11866 (2019) - 2017
- [j3]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. J. Mach. Learn. Res. 18: 195:1-195:38 (2017) - 2016
- [c17]Shai Ben-David, Ruth Urner:
On Version Space Compression. ALT 2016: 50-64 - [c16]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. NIPS 2016: 856-864 - [c15]Anastasia Pentina, Ruth Urner:
Lifelong Learning with Weighted Majority Votes. NIPS 2016: 3612-3620 - [r1]Maria-Florina Balcan, Ruth Urner:
Active Learning - Modern Learning Theory. Encyclopedia of Algorithms 2016: 8-13 - [i5]Aryeh Kontorovich, Sivan Sabato, Ruth Urner:
Active Nearest-Neighbor Learning in Metric Spaces. CoRR abs/1605.06792 (2016) - [i4]Maria-Florina Balcan, Shai Ben-David, Ruth Urner, Ulrike von Luxburg:
Foundations of Unsupervised Learning (Dagstuhl Seminar 16382). Dagstuhl Reports 6(9): 94-109 (2016) - 2015
- [c14]Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner:
Efficient Learning of Linear Separators under Bounded Noise. COLT 2015: 167-190 - [c13]Samory Kpotufe, Ruth Urner, Shai Ben-David:
Hierarchical Label Queries with Data-Dependent Partitions. COLT 2015: 1176-1189 - [c12]Christopher Berlind, Ruth Urner:
Active Nearest Neighbors in Changing Environments. ICML 2015: 1870-1879 - [i3]Pranjal Awasthi, Maria-Florina Balcan, Nika Haghtalab, Ruth Urner:
Efficient Learning of Linear Separators under Bounded Noise. CoRR abs/1503.03594 (2015) - 2014
- [j2]Shai Ben-David, Ruth Urner:
Domain adaptation-can quantity compensate for quality? Ann. Math. Artif. Intell. 70(3): 185-202 (2014) - [c11]Shai Ben-David, Ruth Urner:
The sample complexity of agnostic learning under deterministic labels. COLT 2014: 527-542 - [c10]Shai Ben-David, Ruth Urner:
The sample complexity of agnostic learning with deterministic labels. ISAIM 2014 - [c9]Maria-Florina Balcan, Amit Daniely, Ruta Mehta, Ruth Urner, Vijay V. Vazirani:
Learning Economic Parameters from Revealed Preferences. WINE 2014: 338-353 - [i2]Maria-Florina Balcan, Amit Daniely, Ruta Mehta, Ruth Urner, Vijay V. Vazirani:
Learning Economic Parameters from Revealed Preferences. CoRR abs/1407.7937 (2014) - 2013
- [b1]Ruth Urner:
Learning with non-Standard Supervision. University of Waterloo, Ontario, Canada, 2013 - [c8]Ruth Urner, Sharon Wulff, Shai Ben-David:
PLAL: Cluster-based active learning. COLT 2013: 376-397 - [c7]Sharon Wulff, Ruth Urner, Shai Ben-David:
Monochromatic Bi-Clustering. ICML (2) 2013: 145-153 - [c6]Tameem Adel, Benn Smith, Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte:
Generative Multiple-Instance Learning Models For Quantitative Electromyography. UAI 2013 - [i1]Tameem Adel, Benn Smith, Ruth Urner, Daniel W. Stashuk, Daniel J. Lizotte:
Generative Multiple-Instance Learning Models For Quantitative Electromyography. CoRR abs/1309.6811 (2013) - 2012
- [c5]Shai Ben-David, Ruth Urner:
On the Hardness of Domain Adaptation and the Utility of Unlabeled Target Samples. ALT 2012: 139-153 - [c4]Shai Ben-David, Shai Shalev-Shwartz, Ruth Urner:
Domain Adaptation--Can Quantity compensate for Quality?. ISAIM 2012 - [c3]Ruth Urner, Shai Ben-David, Ohad Shamir:
Learning from Weak Teachers. AISTATS 2012: 1252-1260 - 2011
- [c2]Ruth Urner, Shai Shalev-Shwartz, Shai Ben-David:
Access to Unlabeled Data can Speed up Prediction Time. ICML 2011: 641-648 - 2010
- [j1]Haiko Müller, Ruth Urner:
On a disparity between relative cliquewidth and relative NLC-width. Discret. Appl. Math. 158(7): 828-840 (2010) - [c1]Colleen Swanson, Ruth Urner, Edward Lank:
Naïve Security in a Wi-Fi World. IFIPTM 2010: 32-47
Coauthor Index
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