xgboost: Extreme Gradient Boosting (2017) T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... R package version 0.6-4, 2015 | 3716* | 2015 |

Accelerating the XGBoost algorithm using GPU computing R Mitchell, E Frank PeerJ Computer Science 3, e127, 2017 | 289 | 2017 |

xgboost: Extreme gradient boosting. R package version 0.90. 0.1 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... | 86 | 2020 |

Sampling permutations for Shapley value estimation R Mitchell, J Cooper, E Frank, G Holmes Journal of Machine Learning Research 23 (43), 1-46, 2022 | 81 | 2022 |

Adaptive XGBoost for evolving data streams J Montiel, R Mitchell, E Frank, B Pfahringer, T Abdessalem, A Bifet 2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020 | 52 | 2020 |

Xgboost: Scalable GPU accelerated learning R Mitchell, A Adinets, T Rao, E Frank arXiv preprint arXiv:1806.11248, 2018 | 51 | 2018 |

GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles R Mitchell, E Frank, G Holmes PeerJ Computer Science 8, e880, 2022 | 44 | 2022 |

xgboost: Extreme gradient boosting. R package version 0.90. 0.2 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... | 34 | 2019 |

Gradient boosting, decision trees and XGBoost with CUDA R Mitchell NVIDIA Developer Blog, 2018 | 13 | 2018 |

Gputreeshap: Fast parallel tree interpretability R Mitchell, E Frank, G Holmes arXiv e-prints, arXiv: 2010.13972, 2020 | 7 | 2020 |

xgboost: Extreme Gradient Boosting; 2019. R package version 1.0. 0.2 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... | 7 | |

An Empirical Study of Moment Estimators for Quantile Approximation R Mitchell, E Frank, G Holmes ACM Transactions on Database Systems (TODS) 46 (1), 1-21, 2021 | 6 | 2021 |

Bandwidth-Optimal Random Shuffling for GPUs R Mitchell, D Stokes, E Frank, G Holmes ACM Transactions on Parallel Computing 9 (1), 1-20, 2022 | 5 | 2022 |

xgboost: Extreme Gradient Boosting R Package Version 1.0. 0.2. 2020 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... | 3 | |

High-throughput machine learning algorithms R Mitchell The University of Waikato, 2021 | | 2021 |

Bias Variance Decompositions using XGBoost R Mitchell | | |

xgboost: Extreme Gradient Boosting. 2020 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... R package version 1 (0.2), 0 | | |

Unsupervised Clustering of Sparse Data in Futhark TS Grenzdörffer, CE Oancea, R Mitchell | | |