Discrete temporal models of social networks S Hanneke, W Fu, EP Xing | 630 | 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 | 361 | 2007 |

Theory of disagreement-based active learning S Hanneke Foundations and Trends® in Machine Learning 7 (2-3), 131-309, 2014 | 359 | 2014 |

The true sample complexity of active learning MF Balcan, S Hanneke, JW Vaughan Machine learning 80, 111-139, 2010 | 212 | 2010 |

A theory of transfer learning with applications to active learning L Yang, S Hanneke, J Carbonell Machine learning 90, 161-189, 2013 | 192 | 2013 |

Rates of convergence in active learning S Hanneke The Annals of Statistics, 333-361, 2011 | 171 | 2011 |

The optimal sample complexity of PAC learning S Hanneke Journal of Machine Learning Research 17 (38), 1-15, 2016 | 167 | 2016 |

Vc classes are adversarially robustly learnable, but only improperly O Montasser, S Hanneke, N Srebro Conference on Learning Theory, 2512-2530, 2019 | 161 | 2019 |

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 | 146 | 2007 |

Minimax analysis of active learning. S Hanneke, L Yang J. Mach. Learn. Res. 16 (1), 3487-3602, 2015 | 130 | 2015 |

Theoretical foundations of active learning S Hanneke Carnegie Mellon University, 2009 | 130 | 2009 |

Discrete temporal models of social networks S Hanneke, EP Xing ICML Workshop on Statistical Network Analysis, 115-125, 2006 | 114 | 2006 |

Teaching dimension and the complexity of active learning S Hanneke International conference on computational learning theory, 66-81, 2007 | 102 | 2007 |

On the value of target data in transfer learning S Hanneke, S Kpotufe Advances in Neural Information Processing Systems 32, 2019 | 88 | 2019 |

Activized learning: Transforming passive to active with improved label complexity S Hanneke The Journal of Machine Learning Research 13 (1), 1469-1587, 2012 | 66 | 2012 |

A theory of universal learning O Bousquet, S Hanneke, S Moran, R Van Handel, A Yehudayoff Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 57 | 2021 |

Universal Bayes consistency in metric spaces S Hanneke, A Kontorovich, S Sabato, R Weiss 2020 Information Theory and Applications Workshop (ITA), 1-33, 2020 | 57 | 2020 |

Proper learning, Helly number, and an optimal SVM bound O Bousquet, S Hanneke, S Moran, N Zhivotovskiy Conference on Learning Theory, 582-609, 2020 | 56 | 2020 |

Adaptive Rates of Convergence in Active Learning. S Hanneke COLT, 2009 | 56 | 2009 |

A no-free-lunch theorem for multitask learning S Hanneke, S Kpotufe The Annals of Statistics 50 (6), 3119-3143, 2022 | 53 | 2022 |