Machine Learning
in Journal Posted on November 4, 2020Journal Ranking & Metrics
Impact Score : | 5.78 |
G2R H-Index : | 15 |
JCR Impact Factor : | 2.672 |
Scopus Citescore : | 5 |
SCIMAGO SJR : | 1.034 |
SCIMAGO H-index : | 144 |
Guide2Research Overall Ranking : | 130 |
Journal Information
ISSN : | 0885-6125 |
Publisher : |
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Periodicity : | Monthly |
Editors-in-Chief : | Hendrik Blockeel |
Journal & Submission Website : | https://www.springer.com/journal/10994 |
Top Scientists who published in this Journal
Number of top scientists* : | 46 |
Documents published by top scientists* : | 65 |
* Based on data published during the last three years. |
Aims & Scope of the Journal
Machine Learning publishes original research documents in the areas of Machine Learning & Artificial intelligence. The journal is intended for academics, practitioners and researchers who are interested in such subjects of academic research . The publishing process for Machine Learning is to publish new original papers that have been appropriately reviewed by skilled scientific experts. The journal welcomes submissions from the research community where emphasis will be placed on the novelty and the practical significance of the reported work.
Machine Learning is covered by a wide range of abstracting/indexing services including Scopus, Journal Citation Reports ( Clarivate ) and Guide2Research. A number of prominent scholars considered this journal to publish their scholarly documents including Masashi Sugiyama, Ivor W. Tsang, Zhi-Hua Zhou and Luc De Raedt.
For additional information on the guidelines and submission requirements for authors, you are advised to see the official website for the journal for Machine Learning at https://www.springer.com/journal/10994 .
Special Issues on this journal
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Safe and Fair Machine LearningMachine Learning |
Tue 15 Feb 2022 |
Closed Special Issues
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Foundations of Data ScienceMachine Learning |
Mon 01 Mar 2021 |
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Discovery Science 2020Machine Learning |
Fri 01 Jan 2021 |
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Robust Machine LearningMachine Learning |
Mon 17 Aug 2020 |
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Machine Learning for Earth Observation DataMachine Learning |
Mon 15 Jun 2020 |
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Reinforcement Learning for Real LifeMachine Learning |
Fri 15 May 2020 |