Ruth Urner
Ruth Urner
Associate Professor, York University, Toronto
Verified email at - Homepage
Cited by
Cited by
Efficient learning of linear separators under bounded noise
P Awasthi, MF Balcan, N Haghtalab, R Urner
Conference on Learning Theory, 167-190, 2015
On the hardness of domain adaptation and the utility of unlabeled target samples
S Ben-David, R Urner
Algorithmic Learning Theory: 23rd International Conference, ALT 2012, Lyon …, 2012
Domain adaptation–can quantity compensate for quality?
S Ben-David, R Urner
Annals of Mathematics and Artificial Intelligence 70, 185-202, 2014
Plal: Cluster-based active learning
R Urner, S Wulff, S Ben-David
Conference on Learning Theory, 376-397, 2013
Access to unlabeled data can speed up prediction time
R Urner, S Shalev-Shwartz, S Ben-David
Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011
Learning economic parameters from revealed preferences
MF Balcan, A Daniely, R Mehta, R Urner, VV Vazirani
Web and Internet Economics: 10th International Conference, WINE 2014 …, 2014
Learning from weak teachers
R Urner, SB David, O Shamir
Artificial intelligence and statistics, 1252-1260, 2012
Active nearest neighbors in changing environments
C Berlind, R Urner
International conference on machine learning, 1870-1879, 2015
Lifelong learning with weighted majority votes
A Pentina, R Urner
Advances in Neural Information Processing Systems 29, 2016
Probabilistic lipschitzness a niceness assumption for deterministic labels
R Urner, S Ben-David
Learning Faster from Easy Data-Workshop@ NIPS 2, 1, 2013
Active nearest-neighbor learning in metric spaces
A Kontorovich, S Sabato, R Urner
Journal of Machine Learning Research 18 (195), 1-38, 2018
When can unlabeled data improve the learning rate?
C Göpfert, S Ben-David, O Bousquet, S Gelly, I Tolstikhin, R Urner
Conference on Learning Theory, 1500-1518, 2019
Active Learning-Modern Learning Theory.
MF Balcan, R Urner
Encyclopedia of algorithms, 8-13, 2016
Black-box certification and learning under adversarial perturbations
H Ashtiani, V Pathak, R Urner
International Conference on Machine Learning, 388-398, 2020
On learnability wih computable learners
S Agarwal, N Ananthakrishnan, S Ben-David, T Lechner, R Urner
Algorithmic Learning Theory, 48-60, 2020
Domain adaptation as learning with auxiliary information
S Ben-David, R Urner
New directions in transfer and multi-task-workshop@ NIPS, 2013
Naïve security in a Wi-Fi world
C Swanson, R Urner, E Lank
Trust Management IV: 4th IFIP WG 11.11 International Conference, IFIPTM 2010 …, 2010
Hierarchical label queries with data-dependent partitions
S Kpotufe, R Urner, S Ben-David
Conference on Learning Theory, 1176-1189, 2015
Learning losses for strategic classification
T Lechner, R Urner
Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7337-7344, 2022
Generative multiple-instance learning models for quantitative electromyography
T Adel, B Smith, R Urner, D Stashuk, DJ Lizotte
arXiv preprint arXiv:1309.6811, 2013
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