Automatic Gradient Boosting

The weka data mining software: An update

Mark Hall, Eibe Frank, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, and Ian H. Witten · 1931

Earlier work this paper cites.

A preprocessing scheme for high-cardinality categorical attributes in classification and prediction problems

Daniele Micci-Barreca · 1931

Earlier work this paper cites.

Generalized simulated annealing

Constantino Tsallis and Daniel A. Stariolo · 1996

Earlier work this paper cites.

Greedy function approximation: A gradient boosting machine

Jerome H. Friedman · 2001

Earlier work this paper cites.

Mcrank: Learning to rank using multiple classification and gradient boosting

Ping Li, Qiang Wu, and Christopher J Burges · 2008

Earlier work this paper cites.

Sequential Model-Based Optimization for General Algorithm Configuration , pages 507–523

Frank Hutter, Holger H. Hoos, and Kevin Leyton-Brown · 2011

Earlier work this paper cites.

Practical bayesian optimization of machine learning algorithms

Jasper Snoek, Hugo Larochelle, and Ryan P Adams · 2012

Earlier work this paper cites.

A gradient boosting algorithm for survival analysis via direct optimization of concordance index

Yifei Chen, Zhenyu Jia, Dan Mercola, and Xiaohui Xie · 2013

Earlier work this paper cites.

Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms

C. Thornton, F. Hutter, H. H. Hoos, and K. Leyton-Brown · 2013

Cited alongside, same era.

MOI-MBO: multiobjective infill for parallel model-based optimization

Bernd Bischl, Simon Wessing, Nadja Bauer, Klaus Friedrichs, and Claus Weihs · 2014

Cited alongside, same era.

Simultaneous model selection and optimization through parameter-free stochastic learning

Francesco Orabona · 2014

Cited alongside, same era.

Openml: networked science in machine learning

Original

Joaquin Vanschoren, Jan N Van Rijn, Bernd Bischl, and Luis Torgo · 2014

Cited alongside, same era.

Efficient and robust automated machine learning

Matthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Springenberg, Manuel Blum, and Frank Hutter · 2015

Cited alongside, same era.

XGBoost: A scalable tree boosting system

Tianqi Chen and Carlos Guestrin · 2016

Later among the works it cites.

Multi-objective parameter configuration of machine learning algorithms using model-based optimization

Daniel Horn and Bernd Bischl · 2016

Later among the works it cites.

Automating biomedical data science through tree-based pipeline optimization

Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, and Jason H. Moore · 2016

Later among the works it cites.

mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions , 2017

Bernd Bischl, Jakob Richter, Jakob Bossek, Daniel Horn, Janek Thomas, and Michel Lang · 2017

Later among the works it cites.

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

Later among the works it cites.