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Gradient Boosted Decision Trees (GBDT) is a very successful ensemble learning algorithm widely used across a variety of applications.
A tree-structured approach to nonparametric multiple regression
Jerome H Friedman · 1979
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Induction of decision trees
J. Ross Quinlan · 1986
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Learning with continuous classes
John R Quinlan et al · 1992
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Induction of model trees for predicting continuous classes
Y. Wang and I. H. Witten · 1997
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Vector architectures: past, present and future
Roger Espasa, Mateo Valero, and James E Smith · 1998
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Additive logistic regression: a statistical view of boosting (with discussion and a rejoinder by the authors)
Jerome Friedman, Trevor Hastie, Robert Tibshirani, et al · 2000
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Greedy function approximation: a gradient boosting machine
Jerome H Friedman · 2001
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Secret: a scalable linear regression tree algorithm
Alin Dobra and Johannes Gehrke · 2002
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A simple regression based heuristic for learning model trees
Celine Vens and Hendrik Blockeel · 2006
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Scalable look-ahead linear regression trees
David S Vogel, Ognian Asparouhov, and Tobias Scheffer · 2007
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The weka data mining software: an update
Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H Witten · 2009
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Parallel boosted regression trees for web search ranking
Stephen Tyree, Kilian Q Weinberger, Kunal Agrawal, and Jennifer Paykin · 2011
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Combining factorization model and additive forest for collaborative followee recommendation
Tianqi Chen, Linpeng Tang, Qin Liu, Diyi Yang, Saining Xie, Xuezhi Cao, Chunyang Wu, Enpeng Yao, Zhengyang Liu, Zhansheng Jiang, et al · 2012
Cited alongside, same era.
Cubist models for regression
Max Kuhn, Steve Weston, Chris Keefer, and Nathan Coulter · 2012
Cited alongside, same era.
C4. 5: programs for machine learning
J Ross Quinlan · 2014
Cited alongside, same era.
Intel math kernel library
Endong Wang, Qing Zhang, Bo Shen, Guangyong Zhang, Xiaowei Lu, Qing Wu, and Yajuan Wang · 2014
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XGBoost: A scalable tree boosting system
Tianqi Chen and Carlos Guestrin · 2016
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Classification and Regression Trees
Leo Breiman · 2017
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Lightgbm: A highly efficient gradient boosting decision tree
Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, and Tie-Yan Liu · 2017
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GPU-acceleration for large-scale tree boosting
Huan Zhang, Si Si, and Cho-Jui Hsieh · 2017
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Package ‘cubist’
Max Kuhn, Steve Weston, Chris Keefer, and Maintainer Max Kuhn · 2018
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A convergence rate analysis for logitboost, mart and their variant
Peng Sun, Tong Zhang, and Jie Zhou · 2014
Cited alongside, same era.
Boosted varying-coefficient regression models for product demand prediction
Jianqiang C Wang and Trevor Hastie · 2014
Cited alongside, same era.
Liudmila Prokhorenkova, Gleb Gusev, Aleksandr Vorobev, Anna Veronika Dorogush, and Andrey Gulin · 2018
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Efficient gradient boosted decision tree training on GPUs
Zeyi Wen, Bingsheng He, Ramamohanarao Kotagiri, Shengliang Lu, and Jiashuai Shi · 2018
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