
Machine Learning is an international forum for research on computational approaches to learning. The journal publishes articles reporting substantive results on a wide range of learning methods applied to a variety of learning problems.
The journal features papers that describe research on problems and methods, applications research, and issues of research methodology. Papers making claims about learning problems or methods provide solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena. Applications papers show how to apply learning methods to solve important applications problems. Research methodology papers improve how machine learning research is conducted.
All papers describe the supporting evidence in ways that can be verified or replicated by other researchers. The papers also detail the learning component clearly and discuss assumptions regarding knowledge representation and the performance task.
- An international forum for research on computational approaches to learning.
- Reports substantive results on a wide range of learning methods applied to a variety of learning problems.
- Provides solid support via empirical studies, theoretical analysis, or comparison to psychological phenomena.
- Shows how to apply learning methods to solve important applications problems.
- Improves how machine learning research is conducted.
Journal information
- Editor-in-Chief
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- Peter A. Flach
- Publishing model
- Hybrid. Open Access options available
Journal metrics
- 2.809 (2018)
- Impact factor
- 3.203 (2018)
- Five year impact factor
- 61 days
- Submission to first decision
- 18 days
- Acceptance to publication
- 659,611 (2018)
- Downloads
Latest articles
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Exploiting causality in gene network reconstruction based on graph embedding
Authors (first, second and last of 4)
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Logical reduction of metarules
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Inductive general game playing
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Journal updates
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Call for Papers: Special Issue on Reinforcement Learning for Real Life
Guest Editors: Alborz Geramifard, Lihong Li, Yuxi Li, Csaba Szepesvari, Tao Wang
Submission deadline: March 5, 2020
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Call for Papers: Special Issue on Inductive Logic Programming, ILP 2020
Guest editors: Nikos Katzouris, Alexander Artikis
Journal track Cut-off dates: 10 October 2019, 10 February 2020.
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Call for Papers: Special Issue on Feature Engineering
Guest Editors: Tim Verdonck, Bart Baesens, María Óskarsdóttir, Seppe vanden Broucke
Submission deadline: March 1st, 2020
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Call for Papers: Special Issue on Machine Learning for Earth Observation Data
Guest Editors: Thomas Corpetti, Dino Ienco, Roberto Interdonato, Sébastien Lefèvre, Minh-Tan Pham
Submission deadline: April 1st, 2020
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- Immediate online access
- Full Journal access includes all articles
- Downloadable in PDF
- Subscription expires 12/31/2019
About this journal
- Electronic ISSN
- 1573-0565
- Print ISSN
- 0885-6125
- Abstracted and indexed in
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- ACM Digital Library
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- Copyright information
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© The Author(s), under exclusive licence to Springer Science+Business Media LLC, part of Springer Nature