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Discipline | Machine learning |
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Language | English |
Publication details | |
History | 1986ββto present |
Publisher | |
2.809 (2018) | |
Standard abbreviations ISO 4 (alt) · Bluebook (alt1 · alt2) NLM (alt) · MathSciNet (alt ![]() | |
ISO 4 | Mach. Learn. |
Indexing CODEN (alt · alt2) · JSTOR (alt) · LCCN (alt) MIAR · NLM (alt) · Scopus | |
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 orderββto support theββJournal 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."
Following the mass resignation, Kluwer changed their publishing policy to allow authors to self-archive their papers online after peer-review.
Selected articlesβ»
- J.R. Quinlan (1986). "Induction of Decision Trees". Machine Learning. 1: 81β106. doi:10.1007/BF00116251.
- Nick Littlestone (1988). "Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm" (PDF). Machine Learning. 2 (4): 285β318. doi:10.1007/BF00116827.
- John R. Anderson and Michael Matessa (1992). "Explorations of an Incremental, Bayesian Algorithm for Categorization". Machine Learning. 9 (4): 275β308. doi:10.1007/BF00994109.
- David Klahr (1994). "Children, Adults, and Machines as Discovery Systems". Machine Learning. 14 (3): 313β320. 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: 81β108. doi:10.1007/BF00993822.
- Luc De Raedt and Luc Dehaspe (1997). "Clausal Discovery". Machine Learning. 26 (2/3): 99β146. doi:10.1023/A:1007361123060.
- C. de la Higuera (1997). "Characteristic Sets for Grammatical Inference". Machine Learning. 27: 1β14.
- Robert E. Schapire and Yoram Singer (1999). "Improved Boosting Algorithms Using Confidence-rated Predictions". Machine Learning. 37 (3): 297β336. 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): 135β168. doi:10.1023/A:1007649029923.
- P. Rossmanith and T. Zeugmann (2001). "Stochastic Finite Learning of the Pattern Languages". Machine Learning. 44 (1β2): 67β91. doi:10.1023/A:1010875913047.
- Parekh, Rajesh; Honavar, Vasant (2001). "Learning DFA from Simple Examples". Machine Learning. 44 (1/2): 9β35. 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: 225β254. doi:10.1023/A:1012470815092.
- Simon Colton and Stephen Muggleton (2006). "Mathematical Applications of Inductive Logic Programming" (PDF). Machine Learning. 64 (1β3): 25β64. 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 (2β3): 121β133. doi:10.1007/s10994-007-5029-3.
Referencesβ»
- ^ "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).
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