| Discrete temporal models of social networks S Hanneke, W Fu, EP Xing | 521 | 2010 |
| A bound on the label complexity of agnostic active learning S Hanneke Proceedings of the 24th international conference on Machine learning, 353-360, 2007 | 331 | 2007 |
| Theory of disagreement-based active learning S Hanneke Foundations and TrendsŪ in Machine Learning 7 (2-3), 131-309, 2014 | 276 | 2014 |
| The true sample complexity of active learning MF Balcan, S Hanneke, JW Vaughan Machine learning 80, 111-139, 2010 | 197 | 2010 |
| Rates of convergence in active learning S Hanneke The Annals of Statistics, 333-361, 2011 | 145 | 2011 |
| 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 | 141 | 2007 |
| A theory of transfer learning with applications to active learning L Yang, S Hanneke, J Carbonell Machine learning 90, 161-189, 2013 | 135 | 2013 |
| The optimal sample complexity of PAC learning S Hanneke The Journal of Machine Learning Research 17 (1), 1319-1333, 2016 | 128 | 2016 |
| Theoretical foundations of active learning S Hanneke Carnegie Mellon University, 2009 | 121 | 2009 |
| Discrete temporal models of social networks S Hanneke, EP Xing Statistical network analysis: models, issues, and new directions: ICML 2006 …, 2007 | 106 | 2007 |
| Vc classes are adversarially robustly learnable, but only improperly O Montasser, S Hanneke, N Srebro Conference on Learning Theory, 2512-2530, 2019 | 102 | 2019 |
| Minimax analysis of active learning. S Hanneke, L Yang J. Mach. Learn. Res. 16 (1), 3487-3602, 2015 | 94 | 2015 |
| Teaching dimension and the complexity of active learning S Hanneke Learning Theory: 20th Annual Conference on Learning Theory, COLT 2007, San …, 2007 | 93 | 2007 |
| Activized learning: Transforming passive to active with improved label complexity S Hanneke The Journal of Machine Learning Research 13, 1469-1587, 2012 | 60 | 2012 |
| Adaptive Rates of Convergence in Active Learning. S Hanneke COLT, 2009 | 53 | 2009 |
| Network completion and survey sampling S Hanneke, EP Xing Artificial intelligence and statistics, 209-215, 2009 | 50 | 2009 |
| On the value of target data in transfer learning S Hanneke, S Kpotufe Advances in Neural Information Processing Systems 32, 2019 | 38 | 2019 |
| Robust interactive learning MF Balcan, S Hanneke Conference on Learning Theory, 20.1-20.34, 2012 | 38 | 2012 |
| Surrogate losses in passive and active learning S Hanneke, L Yang | 34 | 2019 |
| Refined error bounds for several learning algorithms S Hanneke The Journal of Machine Learning Research 17 (1), 4667-4721, 2016 | 34 | 2016 |
