Challenges and Opportunities of Building Fast GBDT Systems

Wen, Zeyi; Li, Qinbin; He, Bingsheng; Cui, Bin

doi:10.24963/ijcai.2021/632

Challenges and Opportunities of Building Fast GBDT Systems

Zeyi Wen, Qinbin Li, Bingsheng He, Bin Cui

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Survey Track. Pages 4661-4668.

https://doi.org/10.24963/ijcai.2021/632

Keywords

Machine learning: General

Abstract

In the last few years, Gradient Boosting Decision Trees (GBDTs) have been widely used in various applications such as online advertising and spam filtering. However, GBDT training is often a key performance bottleneck for such data science pipelines, especially for training a large number of deep trees on large data sets. Thus, many parallel and distributed GBDT systems have been researched and developed to accelerate the training process. In this survey paper, we review the recent GBDT systems with respect to accelerations with emerging hardware as well as cluster computing, and compare the advantages and disadvantages of the existing implementations. Finally, we present the research opportunities and challenges in designing fast next generation GBDT systems.

Zeyi Wen, Qinbin Li, Bingsheng He, and Bin Cui. 2021. Challenges and Opportunities of Building Fast GBDT Systems. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 4661–4668. https://doi.org/10.24963/ijcai.2021/632

@inproceedings{ijcai2021p632,
  title     = {Challenges and Opportunities of Building Fast GBDT Systems},
  author    = {Wen, Zeyi and Li, Qinbin and He, Bingsheng and Cui, Bin},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Prof. Zhi-Hua Zhou},
  pages     = {4661--4668},
  year      = {2021},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2021/632},
  url       = {https://doi.org/10.24963/ijcai.2021/632},
}

TY  - CPAPER
TI  - Challenges and Opportunities of Building Fast GBDT Systems
AU  - Wen, Zeyi
AU  - Li, Qinbin
AU  - He, Bingsheng
AU  - Cui, Bin
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 4661
EP  - 4668
DO  - 10.24963/ijcai.2021/632
UR  - https://doi.org/10.24963/ijcai.2021/632
ER  -