Machine Learning (journal)
.jpg) | |
| Discipline | Machine learning |
|---|---|
| Language | English |
| Publication details | |
| History | 1986 to present |
| Publisher | |
| 2.809 (2018) | |
| Standard abbreviations | |
| ISO 4 | Mach. Learn. |
| Indexing | |
| ISSN | 1573-0565 |
| Links | |
Machine Learning is a peer-reviewed scientific journal, published since 1986.
In 2001, forty editors and members of the editorial board of Machine Learning resigned in order to support the Journal of Machine Learning Research (JMLR), saying that in the era of the internet, it was detrimental for researchers to continue publishing their papers in expensive journals with pay-access archives. Instead, they wrote, they supported the model of JMLR, in which authors retained copyright over their papers and archives were freely available on the internet.[1]
Following the mass resignation, Kluwer changed their publishing policy to allow authors to self-archive their papers online after peer-review.[2]
Abstracting and indexing
The journal is abstracted and indexed in several databases, for example in:[3]
Selected articles
- J.R. Quinlan (1986). "Induction of Decision Trees". Machine Learning. 1: 81–106. doi:10.1007/BF00116251.
- Nick Littlestone (1988). "Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm" (PDF). Machine Learning. 2 (4): 285–318. doi:10.1007/BF00116827. Archived from the original (PDF) on 2022-07-02. Retrieved 2020-02-22.
- John R. Anderson and Michael Matessa (1992). "Explorations of an Incremental, Bayesian Algorithm for Categorization". Machine Learning. 9 (4): 275–308. doi:10.1007/BF00994109.
- David Klahr (1994). "Children, Adults, and Machines as Discovery Systems". Machine Learning. 14 (3): 313–320. doi:10.1007/BF00993981.
- Thomas Dean and Dana Angluin and Kenneth Basye and Sean Engelson and Leslie Kaelbling and Evangelos Kokkevis and Oded Maron (1995). "Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning". Machine Learning. 18: 81–108. doi:10.1007/BF00993822.
- Luc De Raedt and Luc Dehaspe (1997). "Clausal Discovery". Machine Learning. 26 (2/3): 99–146. doi:10.1023/A:1007361123060.
- C. de la Higuera (1997). "Characteristic Sets for Grammatical Inference". Machine Learning. 27: 1–14.
- Robert E. Schapire and Yoram Singer (1999). "Improved Boosting Algorithms Using Confidence-rated Predictions". Machine Learning. 37 (3): 297–336. doi:10.1023/A:1007614523901.
- Robert E. Schapire and Yoram Singer (2000). "BoosTexter: A Boosting-based System for Text Categorization". Machine Learning. 39 (2/3): 135–168. doi:10.1023/A:1007649029923.
- P. Rossmanith and T. Zeugmann (2001). "Stochastic Finite Learning of the Pattern Languages". Machine Learning. 44 (1–2): 67–91. doi:10.1023/A:1010875913047.
- Parekh, Rajesh; Honavar, Vasant (2001). "Learning DFA from Simple Examples". Machine Learning. 44 (1/2): 9–35. doi:10.1023/A:1010822518073.
- Ayhan Demiriz and Kristin P. Bennett and John Shawe-Taylor (2002). "Linear Programming Boosting via Column Generation". Machine Learning. 46: 225–254. doi:10.1023/A:1012470815092.
- Simon Colton and Stephen Muggleton (2006). "Mathematical Applications of Inductive Logic Programming" (PDF). Machine Learning. 64 (1–3): 25–64. doi:10.1007/s10994-006-8259-x.
- Will Bridewell and Pat Langley and Ljupco Todorovski and Saso Dzeroski (2008). "Inductive Process Modeling". Machine Learning.
- Stephen Muggleton and Alireza Tamaddoni-Nezhad (2008). "QG/GA: a stochastic search for Progol". Machine Learning. 70 (2–3): 121–133. doi:10.1007/s10994-007-5029-3.
References
- ^ "Editorial Board of the Kluwer Journal, Machine Learning: Resignation Letter". SIGIR Forum. 35 (2). 2001.
- ^ Robin, Peek (1 December 2001). "Machine Learning's Editorial Board Divided". Information Today. 18 (11). Archived from the original on 13 August 2017. Retrieved 12 August 2017.
- ^ "Machine Learning". MIAR: Information Matrix for the Analysis of Journals. University of Barcelona. Retrieved 2025-06-18.
- ^ "Machine Learning – Abstracting and indexing". Springer Nature. Retrieved 2025-06-18.
- ^ "Machine Learning – Abstracting and indexing". Springer Nature. Retrieved 2025-06-18.
- ^ "Machine Learning – Abstracting and indexing". Springer Nature. Retrieved 2025-06-18.
- ^ "Machine Learning – Abstracting and indexing". Springer Nature. Retrieved 2025-06-18.
- ^ "Machine Learning – Abstracting and indexing". Springer Nature. Retrieved 2025-06-18.
  | This article about a computer science journal is a stub. You can help Wikipedia by adding missing information. See tips for writing articles about academic journals. Further suggestions might be found on the article's talk page. |
 | This machine learning–related article is a stub. You can help Wikipedia by adding missing information. |
Content Disclaimer
Informasi ini disarikan dari Wikipedia dan disajikan kembali untuk tujuan edukasi. Konten tersedia di bawah lisensi CC BY-SA 3.0. Kami tidak bertanggung jawab atas ketidakakuratan data yang bersumber dari kontribusi publik tersebut.
- The information displayed on this website is sourced in part or in whole from Wikipedia and has been adapted for the purpose of restating it. We strive to provide accurate and relevant information, however:
- There is no guarantee of absolute accuracy. Wikipedia is an open, collaborative project that can be edited by anyone, so information is subject to change.
- It is not intended to constitute professional advice. The content displayed is for informational and educational purposes only. For important decisions (e.g., medical, legal, or financial), please consult a professional.
- Content copyright. Wikipedia is licensed under the Creative Commons Attribution-ShareAlike License (CC BY-SA). This means that content may be reused with appropriate attribution and shared under a similar license.
- Responsible use. Any risk arising from the use of information from this website is entirely the responsibility of the user.