| XGBoost: Extreme Gradient Boosting T Chen, T He, M Benesty, V Khotilovich, Y Tang https://CRAN.R-project.org/package=xgboost. R package version 0.6-4, 2016 | 3768 | 2016 |
| ggfortify: Unified Interface to Visualize Statistical Result of Popular R Packages Y Tang, M Horikoshi, W Li R Journal 8 (2), 474-485, 2016 | 690* | 2016 |
| R interface to Keras J Allaire, F Chollet, Y Tang, D Falbel, W Van Der Bijl, M Studer RStudio, Google, 2018 | 518* | 2018 |
| reticulate: R Interface to Python J Allaire, K Ushey, Y Tang, RStudio https://CRAN.R-project.org/package=reticulate. R package version 1 (1), 410, 2018 | 273* | 2018 |
| xgboost: extreme gradient boosting. R package version 0.71. 2 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... Grin Verlag: München, Germnay, 2018 | 248* | 2018 |
| ggfortify: Data visualization tools for statistical analysis results M Horikoshi, Y Tang CRAN R package. https://CRAN.R-project.org/package=ggfortify, 2016 | 220* | 2016 |
| tensorflow: R Interface to TensorFlow JJ Allaire, D Eddelbuettel, N Golding, Y Tang | 181* | 2016 |
| h2o: R interface for the’H2O’Scalable machine learning platform E LeDell, N Gill, S Aiello, A Fu, A Candel, C Click, T Kraljevic, Y Tang, ... R package version 3 (0.1), 2, 2020 | 129* | 2020 |
| caret: Classification and Regression Training. R package M Kuhn, J Wing, S Weston, A Williams, C Keefer, A Engelhardt, T Cooper, ... | 123* | 2016 |
| TF.Learn: TensorFlow's high-level module for distributed machine learning Y Tang arXiv preprint arXiv:1612.04251, 2016 | 85 | 2016 |
| metric-learn: Metric Learning Algorithms in Python W de Vazelhes, CJ Carey, Y Tang, N Vauquier, A Bellet Journal of Machine Learning Research, 2020 | 69 | 2020 |
| TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks HT Cheng, Z Haque, L Hong, M Ispir, C Mewald, I Polosukhin, ... Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 36 | 2017 |
| TensorFlow实战 (TensorFlow in Practice) W Huang, Y Tang Beijing Publishing House of Electronics Industry, 2017 | 36* | 2017 |
| A Scalable and Cloud-Native Hyperparameter Tuning System J George, C Gao, R Liu, HG Liu, Y Tang, R Pydipaty, AK Saha arXiv preprint arXiv:2006.02085, 2020 | 15* | 2020 |
| SQLFlow: A Bridge between SQL and Machine Learning Y Wang, Y Yang, W Zhu, Y Wu, X Yan, Y Liu, Y Wang, L Xie, Z Gao, ... arXiv preprint arXiv:2001.06846, 2020 | 15* | 2020 |
| AnomalyDetection: Anomaly Detection Using Seasonal Hybrid Extreme Studentized Deviate Test OS Vallis, J Hochenbaum, A Kejariwal, B Rudis, Y Tang R package version 1, 2014 | 15 | 2014 |
| lfda: Local Fisher Discriminant Analysis in R Y Tang, W Li Journal of Open Source Software 4 (39), 1572, 2019 | 14* | 2019 |
| Systems and methods for detecting and remedying software anomalies Y Tang, T Li, J Herzog US Patent 10,635,519, 2020 | 7 | 2020 |
| dml: Distance Metric Learning in R Y Tang, T Gao, N Xiao Journal of Open Source Software 3 (30), 1036, 2018 | 6 | 2018 |
| autoplotly: An R Package for Automatic Generation of Interactive Visualizations for Statistical Results Y Tang Journal of Open Source Software 3 (24), 657, 2018 | 6* | 2018 |
Tianqi ChenCarnegie Mellon UniversityVerified email at cmu.edu
