仕訳帳情報

Machine Learning

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インパクト ・ ファクター:
2.9
出版社:
Springer
ISSN:
0885-6125
閲覧:
26601
追跡:
46

論文募集

Machine Learning is an academic journal published by Springer. (ISSN 0885-6125, impact factor 2.9, CCF B).

Aims and scope 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, including but not limited to: Learning Problems: Classification, regression, recognition, and prediction; Problem solving and planning; Reasoning and inference; Data mining; Web mining; Scientific discovery; Information retrieval; Natural language processing; Design and diagnosis; Vision and speech perception; Robotics and control; Combinatorial optimization; Game playing; Industrial, financial, and scientific applications of all kinds. Learning Methods: Supervised and unsupervised learning methods (including learning decision and regression trees, rules, connectionist networks, probabilistic networks and other statistical models, inductive logic programming, case-based methods, ensemble methods, clustering, etc.); Reinforcement learning; Evolution-based methods; Explanation-based learning; Analogical learning methods; Automated knowledge acquisition; Learning from instruction; Visualization of patterns in data; Learning in integrated architectures; Multistrategy learning; Multi-agent learning. Papers describe research on problems and methods, applications research, and issues of research methodology. Papers making claims about learning problems (e.g., inherent complexity) or methods (e.g., relative performance of alternative algorithms) 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 must state their contributions clearly and describe how the contributions are supported. All papers must describe the supporting evidence in ways that can be verified or replicated by other researchers. All papers must describe the learning component clearly, and must discuss assumptions regarding knowledge representation and the performance task. All papers must place their contribution clearly in the context of existing work in machine learning. Variations from these prototypes, such as comprehensive surveys of active research areas, critical reviews of existing work, and book reviews, will be considered provided they make a clear contribution to the field.
最終更新 Dou Sun

関連仕訳帳

CCF完全な名前インパクト ・ ファクター出版社ISSN
Engineering11.6Elsevier2095-8099
aIEEE Transactions on Software Engineering5.6IEEE0098-5589
Interactive Learning Environments5.3Taylor & Francis1049-4820
Journal of Computer Assisted Learning4.6Wiley-Blackwell0266-4909
cData Science and Engineering4.6Springer2364-1185
Language Learning & Technology4.1University of Hawaii Press1094-3501
bMachine Learning2.9Springer0885-6125
Journal of Engineering2.3Hindawi2314-4904
Magnetic Resonance Imaging2.0Elsevier0730-725X
bJournal of Automated Reasoning0.8Springer0168-7433

関連会議

CCFCOREQUALIS省略名完全な名前提出日通知日会議日
cb2ICMLAInternational Conference on Machine Learning and Applications2026-05-152026-06-152026-10-05
ba*a2COLTAnnual Conference on Learning Theory2026-02-042026-05-042026-06-29
aa*a1ICMLInternational Conference on Machine Learning2026-01-232026-07-06
b4ICMLCInternational Conference on Machine Learning and Computing2025-12-302026-01-102026-02-06
aa*a1ICDEInternational Conference on Data Engineering2025-10-272025-12-222026-05-04
b3ICWLInternational Conference on Web-based Learning2025-09-302025-10-202025-11-30
b2MLDMInternational Conference on Machine Learning and Data Mining2025-02-152025-03-202025-07-18
cbACMLAsian Conference on Machine Learning2024-06-262024-09-042024-12-05
cbb1ICWEInternational Conference on Web Engineering2024-01-262024-03-222024-06-17
b4ICBLInternational Conference on Blended Learning2017-02-282017-03-152017-06-27

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