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AlphaD3M: Machine Learning Pipeline Synthesis
Drori, Iddo; Krishnamurthy, Yamuna; Rampin, Remi et al.
2021ICML AutoML Workshop
Peer reviewed
 

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Keywords :
Computer Science - Learning
Abstract :
[en] We introduce AlphaD3M, an automatic machine learning (AutoML) system based on meta reinforcement learning using sequence models with self play. AlphaD3M is based on edit operations performed over machine learning pipeline primitives providing explainability. We compare AlphaD3M with state-of-the-art AutoML systems: Autosklearn, Autostacker, and TPOT, on OpenML datasets. AlphaD3M achieves competitive performance while being an order of magnitude faster, reducing computation time from hours to minutes, and is explainable by design.
Disciplines :
Computer science
Author, co-author :
Drori, Iddo
Krishnamurthy, Yamuna
Rampin, Remi
DE PAULA LOURENCO, Raoni  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SerVal
Piazentin Ono, Jorge
Cho, Kyunghyun
Silva, Claudio
Freire, Juliana
External co-authors :
yes
Language :
English
Title :
AlphaD3M: Machine Learning Pipeline Synthesis
Publication date :
2021
Event name :
ICML AutoML Workshop
Event date :
July 2018
Audience :
International
Peer reviewed :
Peer reviewed
Commentary :
ICML 2018 AutoML Workshop
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