Steve Hanneke
Title
Cited by
Cited by
Year
Discrete temporal models of social networks
S Hanneke, W Fu, EP Xing
Electronic Journal of Statistics 4, 585-605, 2010
3862010
A bound on the label complexity of agnostic active learning
S Hanneke
Proceedings of the 24th international conference on Machine learning, 353-360, 2007
2632007
The true sample complexity of active learning
MF Balcan, S Hanneke, JW Vaughan
Machine learning 80 (2-3), 111-139, 2010
1622010
Recovering temporally rewiring networks: A model-based approach
F Guo, S Hanneke, W Fu, EP Xing
Proceedings of the 24th international conference on Machine learning, 321-328, 2007
1302007
Theory of disagreement-based active learning
S Hanneke
Foundations and TrendsŪ in Machine Learning 7 (2-3), 131-309, 2014
1292014
Rates of convergence in active learning
S Hanneke
The Annals of Statistics 39 (1), 333-361, 2011
1152011
Discrete temporal models of social networks
S Hanneke, EP Xing
ICML Workshop on Statistical Network Analysis, 115-125, 2006
942006
Theoretical foundations of active learning
S Hanneke
CARNEGIE-MELLON UNIV PITTSBURGH PA MACHINE LEARNING DEPT, 2009
922009
Teaching dimension and the complexity of active learning
S Hanneke
International Conference on Computational Learning Theory, 66-81, 2007
832007
The optimal sample complexity of PAC learning
S Hanneke
The Journal of Machine Learning Research 17 (1), 1319-1333, 2016
692016
A theory of transfer learning with applications to active learning
L Yang, S Hanneke, J Carbonell
Machine learning 90 (2), 161-189, 2013
692013
Activized learning: Transforming passive to active with improved label complexity
S Hanneke
The Journal of Machine Learning Research 13 (1), 1469-1587, 2012
502012
Minimax analysis of active learning
S Hanneke, L Yang
The Journal of Machine Learning Research 16 (1), 3487-3602, 2015
482015
Adaptive Rates of Convergence in Active Learning.
S Hanneke
COLT, 2009
422009
Network completion and survey sampling
S Hanneke, EP Xing
Artificial Intelligence and Statistics, 209-215, 2009
402009
Robust interactive learning
MF Balcan, S Hanneke
Conference on Learning Theory, 20.1-20.34, 2012
302012
VC classes are adversarially robustly learnable, but only improperly
O Montasser, S Hanneke, N Srebro
arXiv preprint arXiv:1902.04217, 2019
292019
Surrogate losses in passive and active learning
S Hanneke, L Yang
Electronic Journal of Statistics 13 (2), 4646-4708, 2019
262019
An analysis of graph cut size for transductive learning
S Hanneke
Proceedings of the 23rd international conference on Machine learning, 393-399, 2006
202006
Refined error bounds for several learning algorithms
S Hanneke
The Journal of Machine Learning Research 17 (1), 4667-4721, 2016
172016
The system can't perform the operation now. Try again later.
Articles 1–20