Enhancement of detecting permanent water and temporary water in flood disasters by fusing sentinel-1 and sentinel-2 imagery using deep learning algorithms: Demonstration of … Y Bai, W Wu, Z Yang, J Yu, B Zhao, X Liu, H Yang, E Mas, S Koshimura Remote Sensing 13 (11), 2220, 2021 | 54 | 2021 |

Large scale GPS trajectory generation using map based on two stage GAN X Wang, X Liu, Z Lu, H Yang Journal of Data Science 19 (1), 126-141, 2021 | 42 | 2021 |

Jackknife empirical likelihood inference for the mean absolute deviation Y Zhao, X Meng, H Yang Computational Statistics & Data Analysis 91, 92-101, 2015 | 42 | 2015 |

Two-way partial AUC and its properties H Yang, K Lu, X Lyu, F Hu Statistical methods in medical research 28 (1), 184-195, 2019 | 40 | 2019 |

Smoothed jackknife empirical likelihood inference for the difference of ROC curves H Yang, Y Zhao Journal of Multivariate Analysis 115, 270-284, 2013 | 36 | 2013 |

Smoothed jackknife empirical likelihood inference for ROC curves with missing data H Yang, Y Zhao Journal of Multivariate Analysis 140, 123-138, 2015 | 31 | 2015 |

Nightlight as a proxy of economic indicators: Fine-grained GDP inference around Chinese mainland via attention-augmented CNN from daytime satellite imagery H Liu, X He, Y Bai, X Liu, Y Wu, Y Zhao, H Yang Remote Sensing 13 (11), 2067, 2021 | 26 | 2021 |

Mtrec: Multi-task learning over bert for news recommendation Q Bi, J Li, L Shang, X Jiang, Q Liu, H Yang Findings of the Association for Computational Linguistics: ACL 2022, 2663-2669, 2022 | 22 | 2022 |

A nonparametric approach for partial areas under ROC curves and ordinal dominance curves H Yang, K Lu, Y Zhao Statistica Sinica, 357-371, 2017 | 21 | 2017 |

Smoothed jackknife empirical likelihood for the one-sample difference of quantiles H Yang, Y Zhao Computational Statistics & Data Analysis 120, 58-69, 2018 | 18 | 2018 |

Technical solution discussion for key challenges of operational convolutional neural network-based building-damage assessment from satellite imagery: Perspective from benchmark … J Su, Y Bai, X Wang, D Lu, B Zhao, H Yang, E Mas, S Koshimura Remote Sensing 12 (22), 3808, 2020 | 17 | 2020 |

Smoothed jackknife empirical likelihood for the difference of two quantiles H Yang, Y Zhao Annals of the Institute of Statistical Mathematics 69, 1059-1073, 2017 | 15 | 2017 |

Smoothed empirical likelihood for ROC curves with censored data H Yang, Y Zhao Journal of Multivariate Analysis 109, 254-263, 2012 | 13 | 2012 |

New empirical likelihood inference for linear transformation models H Yang, Y Zhao Journal of Statistical Planning and Inference 142 (7), 1659-1668, 2012 | 13 | 2012 |

Boosted histogram transform for regression Y Cai, H Hang, H Yang, Z Lin International Conference on Machine Learning, 1251-1261, 2020 | 11 | 2020 |

Under-bagging nearest neighbors for imbalanced classification H Hang, Y Cai, H Yang, Z Lin Journal of Machine Learning Research 23 (118), 1-63, 2022 | 9 | 2022 |

Smoothed empirical likelihood inference for the difference of two quantiles with right censoring H Yang, C Yau, Y Zhao Journal of Statistical Planning and Inference 146, 95-101, 2014 | 9 | 2014 |

Jackknife empirical likelihood for linear transformation models with right censoring H Yang, S Liu, Y Zhao Annals of the Institute of Statistical Mathematics 68, 1095-1109, 2016 | 8 | 2016 |

Decision tree for locally private estimation with public data Y Ma, H Zhang, Y Cai, H Yang Advances in Neural Information Processing Systems 36, 2024 | 5 | 2024 |

Gradient boosted binary histogram ensemble for large-scale regression H Hang, T Huang, Y Cai, H Yang, Z Lin arXiv preprint arXiv:2106.01986, 2021 | 5 | 2021 |