Machine Learning (journal)
{{Infobox Journal
| title = Machine Learning
| cover = Machine Learning (journal).jpg
| discipline = Machine learning
| abbreviation = Mach. Learn.
| website = https://www.springer.com/west/home/computer/artificial?SGWID=4-147-70-35726603-0
| country = USA
| history = 1986 to present
| impact = 2.809
| impact-year = 2018
| ISSN = 1573-0565
}}
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.{{cite journal | title = Editorial Board of the Kluwer Journal, Machine Learning: Resignation Letter | journal = SIGIR Forum | volume = 35 | issue = 2 | year = 2001 | url = http://sigir.org/files/forum/F2001/sigirFall01Letters.html}}
Following the mass resignation, Kluwer changed their publishing policy to allow authors to self-archive their papers online after peer-review.{{cite journal|last1=Robin|first1=Peek|title=Machine Learning's Editorial Board Divided|journal=Information Today|date=1 December 2001|volume=18|issue=11|url=https://www.questia.com/magazine/1P3-95801675/machine-learning-s-editorial-board-divided|language=en}}
Selected articles
- {{cite journal | author=J.R. Quinlan | title=Induction of Decision Trees | journal=Machine Learning | volume= 1| pages=81–106 | year=1986 | doi=10.1007/BF00116251 | doi-access=free }}
- {{cite journal | author=Nick Littlestone | title=Learning Quickly When Irrelevant Attributes Abound: A New Linear-threshold Algorithm | journal=Machine Learning | volume=2 | issue=4 | pages=285–318 | year=1988 | doi=10.1007/BF00116827 | url=http://www.cs.utsa.edu/~bylander/cs6243/littlestone1988.pdf | doi-access=free }}
- {{cite journal | author=John R. Anderson and Michael Matessa | title=Explorations of an Incremental, Bayesian Algorithm for Categorization | journal=Machine Learning | volume=9 | issue=4 | pages=275–308 | year=1992 | doi=10.1007/BF00994109 | doi-access=free }}
- {{cite journal | author=David Klahr | title=Children, Adults, and Machines as Discovery Systems | journal=Machine Learning | volume=14 | issue=3 | pages=313–320 | year=1994 | doi=10.1007/BF00993981 | doi-access=free }}
- {{cite journal | author=Thomas Dean and Dana Angluin and Kenneth Basye and Sean Engelson and Leslie Kaelbling and Evangelos Kokkevis and Oded Maron | title=Inferring Finite Automata with Stochastic Output Functions and an Application to Map Learning | journal=Machine Learning | volume=18 | pages=81–108 | year=1995 | doi=10.1007/BF00993822 | doi-access=free }}
- {{cite journal | author=Luc De Raedt and Luc Dehaspe | title=Clausal Discovery | journal=Machine Learning | volume=26 | issue=2/3 | pages=99–146 | year=1997 | doi=10.1023/A:1007361123060 | doi-access=free }}
- {{cite journal | author=C. de la Higuera | title=Characteristic Sets for Grammatical Inference | journal=Machine Learning | volume=27 | pages=1–14 | year=1997 }}
- {{cite journal | author=Robert E. Schapire and Yoram Singer | title=Improved Boosting Algorithms Using Confidence-rated Predictions | journal=Machine Learning | volume=37 | issue=3 | pages=297–336 | year=1999 | doi=10.1023/A:1007614523901 | doi-access=free }}
- {{cite journal | author=Robert E. Schapire and Yoram Singer | title=BoosTexter: A Boosting-based System for Text Categorization | journal=Machine Learning | volume=39 | issue=2/3 | pages=135–168 | year=2000 | doi=10.1023/A:1007649029923 | doi-access=free }}
- {{cite journal | author=P. Rossmanith and T. Zeugmann | title=Stochastic Finite Learning of the Pattern Languages | journal=Machine Learning | volume=44 | number=1–2 | pages=67–91 | year=2001 | doi=10.1023/A:1010875913047 | doi-access=free }}
- {{Cite journal|last1=Parekh|first1=Rajesh|last2=Honavar|first2=Vasant|date=2001|title=Learning DFA from Simple Examples|journal=Machine Learning|volume=44|issue=1/2|pages=9–35|doi=10.1023/A:1010822518073|doi-access=free}}
- {{cite journal | author=Ayhan Demiriz and Kristin P. Bennett and John Shawe-Taylor | title=Linear Programming Boosting via Column Generation | journal=Machine Learning | volume=46 | pages=225–254 | year=2002 | doi=10.1023/A:1012470815092 | doi-access=free }}
- {{cite journal | author=Simon Colton and Stephen Muggleton | title=Mathematical Applications of Inductive Logic Programming | journal=Machine Learning | volume=64 | issue=1–3 | pages=25–64 | year=2006 | doi=10.1007/s10994-006-8259-x | url=http://www.doc.ic.ac.uk/crg/papers/colton_mlj06.pdf | doi-access=free }}
- {{cite journal | author=Will Bridewell and Pat Langley and Ljupco Todorovski and Saso Dzeroski | title=Inductive Process Modeling | journal=Machine Learning | year=2008 }}
- {{cite journal | author=Stephen Muggleton and Alireza Tamaddoni-Nezhad | title=QG/GA: a stochastic search for Progol | journal=Machine Learning | volume=70 | issue=2–3 | pages=121–133 | year=2008 | doi=10.1007/s10994-007-5029-3 | doi-access=free }}