Steve Hanneke
タイトル引用先
Discrete temporal models of social networks
S Hanneke, W Fu, EP Xing
Electronic Journal of Statistics 4, 585-605, 2010
3412010
A bound on the label complexity of agnostic active learning
S Hanneke
Carnegie Mellon University, School of Computer Science, Machine Learning …, 2007
2392007
The true sample complexity of active learning
MF Balcan, S Hanneke, JW Vaughan
Machine learning 80 (2-3), 111-139, 2010
1482010
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
1242007
Theory of disagreement-based active learning
S Hanneke
Foundations and Trends® in Machine Learning 7 (2-3), 131-309, 2014
1082014
Rates of convergence in active learning
S Hanneke
The Annals of Statistics 39 (1), 333-361, 2011
992011
Discrete temporal models of social networks
S Hanneke, EP Xing
ICML Workshop on Statistical Network Analysis, 115-125, 2006
932006
Theoretical foundations of active learning
S Hanneke
CARNEGIE-MELLON UNIV PITTSBURGH PA MACHINE LEARNING DEPT, 2009
792009
Teaching dimension and the complexity of active learning
S Hanneke
International Conference on Computational Learning Theory, 66-81, 2007
752007
A theory of transfer learning with applications to active learning
L Yang, S Hanneke, J Carbonell
Machine learning 90 (2), 161-189, 2013
562013
The optimal sample complexity of PAC learning
S Hanneke
The Journal of Machine Learning Research 17 (1), 1319-1333, 2016
512016
Activized learning: Transforming passive to active with improved label complexity
S Hanneke
Journal of Machine Learning Research 13 (May), 1469-1587, 2012
442012
Network completion and survey sampling
S Hanneke, EP Xing
Artificial Intelligence and Statistics, 209-215, 2009
382009
Adaptive Rates of Convergence in Active Learning.
S Hanneke
COLT, 2009
382009
Minimax analysis of active learning
S Hanneke, L Yang
The Journal of Machine Learning Research 16 (1), 3487-3602, 2015
352015
Robust interactive learning
MF Balcan, S Hanneke
Conference on Learning Theory, 20.1-20.34, 2012
262012
Surrogate losses in passive and active learning
S Hanneke, L Yang
arXiv preprint arXiv:1207.3772, 2012
212012
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
142016
A compression technique for analyzing disagreement-based active learning
Y Wiener, S Hanneke, R El-Yaniv
The Journal of Machine Learning Research 16 (1), 713-745, 2015
112015
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