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Journal of
Machine Learning
Aims and Scope
Journal of Machine Learning (JML) publishes high quality research papers in all areas of machine learning, including innovative algorithms of machine learning, theories of machine learning, important applications of machine learning in AI, natural sciences, social sciences, and engineering etc. The journal emphasizes a balanced coverage of both theory and practice. The journal is published in a timely fashion in electronic form. All articles in JML are open-access and there is no charge for the authors.
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News more
JML's Editor-in-Chief Weinan E was awarded 2023 ICIAM Maxwell Prize. Congratulations!
2022-11-09JML's editorial board is formed in October 2021, and it will begin to publish papers in March, 2022.
2021-12-18 -
Featured Articles more
Reinforcement Learning with Function Approximation: From Linear to Nonlinear
by Jihao Long & Jiequn Han, J. Mach. Learn. , 2 (2023), pp. 161-193.
A Brief Survey on the Approximation Theory for Sequence Modelling
by Haotian Jiang, Qianxiao Li, Zhong Li & Shida Wang, J. Mach. Learn. , 2 (2023), pp. 1-30.
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Review Articles more
A Brief Survey on the Approximation Theory for Sequence Modelling
Haotian Jiang, Qianxiao Li, Zhong Li & Shida Wang, J. Mach. Learn. , 2 (2023), pp. 1-30.