| Accelerating the XGBoost algorithm using GPU computing R Mitchell, E Frank PeerJ Computer Science 3, e127, 2017 | 318 | 2017 |
| 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 | 207* | |
| 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, ... | 194* | 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 | 107 | 2022 |
| Xgboost: Scalable GPU accelerated learning R Mitchell, A Adinets, T Rao, E Frank arXiv preprint arXiv:1806.11248, 2018 | 59 | 2018 |
| 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 | 57 | 2020 |
| GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles R Mitchell, E Frank, G Holmes PeerJ Computer Science 8, e880, 2022 | 51 | 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, ... | 36 | 2019 |
| Gradient boosting, decision trees and XGBoost with CUDA R Mitchell NVIDIA Developer Blog, 2018 | 13 | 2018 |
| 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, ... | 9 | |
| Bandwidth-Optimal Random Shuffling for GPUs R Mitchell, D Stokes, E Frank, G Holmes ACM Transactions on Parallel Computing 9 (1), 1-20, 2022 | 8 | 2022 |
| Gputreeshap: Fast parallel tree interpretability R Mitchell, E Frank, G Holmes arXiv e-prints, arXiv: 2010.13972, 2020 | 7 | 2020 |
| 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 |
| 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 | | |
| Unsupervised Clustering of Sparse Data in Futhark TS Grenzdörffer, CE Oancea, R Mitchell | | |
