Boosting (machine learning) (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Boosting (machine learning)" in English language version.

refsWebsite

Global rank English rank

5doi.org

2^nd place

4semanticscholar.org

11^th place

8^th place

3web.archive.org

1^st place

3ghostarchive.org

32^nd place

21^st place

2upenn.edu

702^nd place

520^th place

2psu.edu

207^th place

136^th place

2princeton.edu

741^st place

577^th place

1berkeley.edu

580^th place

462^nd place

1mit.edu

415^th place

327^th place

1image-net.org

low place

1merl.com

low place

1columbia.edu

488^th place

374^th place

berkeley.edu (Global: 580^th place; English: 462^nd place)

oz.berkeley.edu

Leo Breiman (1996). "BIAS, VARIANCE, AND ARCING CLASSIFIERS" (PDF). TECHNICAL REPORT. Archived from the original (PDF) on 2015-01-19. Retrieved 19 January 2015. Arcing [Boosting] is more successful than bagging in variance reduction

columbia.edu (Global: 488^th place; English: 374^th place)

cs.columbia.edu

Long, Philip M.; Servedio, Rocco A. (March 2010). "Random classification noise defeats all convex potential boosters" (PDF). Machine Learning. 78 (3): 287–304. doi:10.1007/s10994-009-5165-z. S2CID 53861. Archived (PDF) from the original on 2022-10-09. Retrieved 2015-11-17.

doi.org (Global: 2^nd place; English: 2^nd place)

Michael Kearns; Leslie Valiant (1989). "Cryptographic limitations on learning Boolean formulae and finite automata". Proceedings of the twenty-first annual ACM symposium on Theory of computing - STOC '89. Vol. 21. ACM. pp. 433–444. doi:10.1145/73007.73049. ISBN 978-0897913072. S2CID 536357.
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.
Leo Breiman (1998). "Arcing classifier (with discussion and a rejoinder by the author)". Ann. Stat. 26 (3): 801–849. doi:10.1214/aos/1024691079. Schapire (1990) proved that boosting is possible. (Page 823)
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.
Long, Philip M.; Servedio, Rocco A. (March 2010). "Random classification noise defeats all convex potential boosters" (PDF). Machine Learning. 78 (3): 287–304. doi:10.1007/s10994-009-5165-z. S2CID 53861. Archived (PDF) from the original on 2022-10-09. Retrieved 2015-11-17.

ghostarchive.org (Global: 32^nd place; English: 21^st place)

Emer, Eric. "Boosting (AdaBoost algorithm)" (PDF). MIT. Archived (PDF) from the original on 2022-10-09. Retrieved 2018-10-10.
Viola, P.; Jones, M.; Snow, D. (2003). Detecting Pedestrians Using Patterns of Motion and Appearance (PDF). ICCV. Archived (PDF) from the original on 2022-10-09.
Long, Philip M.; Servedio, Rocco A. (March 2010). "Random classification noise defeats all convex potential boosters" (PDF). Machine Learning. 78 (3): 287–304. doi:10.1007/s10994-009-5165-z. S2CID 53861. Archived (PDF) from the original on 2022-10-09. Retrieved 2015-11-17.

image-net.org (Global: low place; English: low place)

"Large Scale Visual Recognition Challenge". December 2017.

merl.com (Global: low place; English: low place)

Viola, P.; Jones, M.; Snow, D. (2003). Detecting Pedestrians Using Patterns of Motion and Appearance (PDF). ICCV. Archived (PDF) from the original on 2022-10-09.

mit.edu (Global: 415^th place; English: 327^th place)

math.mit.edu

Emer, Eric. "Boosting (AdaBoost algorithm)" (PDF). MIT. Archived (PDF) from the original on 2022-10-09. Retrieved 2018-10-10.

princeton.edu (Global: 741^st place; English: 577^th place)

cs.princeton.edu

Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.

psu.edu (Global: 207^th place; English: 136^th place)

citeseerx.ist.psu.edu

Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.

semanticscholar.org (Global: 11^th place; English: 8^th place)

api.semanticscholar.org

Michael Kearns; Leslie Valiant (1989). "Cryptographic limitations on learning Boolean formulae and finite automata". Proceedings of the twenty-first annual ACM symposium on Theory of computing - STOC '89. Vol. 21. ACM. pp. 433–444. doi:10.1145/73007.73049. ISBN 978-0897913072. S2CID 536357.
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.
Long, Philip M.; Servedio, Rocco A. (March 2010). "Random classification noise defeats all convex potential boosters" (PDF). Machine Learning. 78 (3): 287–304. doi:10.1007/s10994-009-5165-z. S2CID 53861. Archived (PDF) from the original on 2022-10-09. Retrieved 2015-11-17.

upenn.edu (Global: 702^nd place; English: 520^th place)

cis.upenn.edu

Michael Kearns(1988); Thoughts on Hypothesis Boosting, Unpublished manuscript (Machine Learning class project, December 1988)
Yoav Freund and Robert E. Schapire (1997); A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting, Journal of Computer and System Sciences, 55(1):119-139

web.archive.org (Global: 1^st place; English: 1^st place)

Leo Breiman (1996). "BIAS, VARIANCE, AND ARCING CLASSIFIERS" (PDF). TECHNICAL REPORT. Archived from the original (PDF) on 2015-01-19. Retrieved 19 January 2015. Arcing [Boosting] is more successful than bagging in variance reduction
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.
Schapire, Robert E. (1990). "The Strength of Weak Learnability" (PDF). Machine Learning. 5 (2): 197–227. CiteSeerX 10.1.1.20.723. doi:10.1007/bf00116037. S2CID 53304535. Archived from the original (PDF) on 2012-10-10. Retrieved 2012-08-23.

Boosting (machine learning) (English Wikipedia)

berkeley.edu (Global: 580th place; English: 462nd place)

oz.berkeley.edu

columbia.edu (Global: 488th place; English: 374th place)

cs.columbia.edu

doi.org (Global: 2nd place; English: 2nd place)

ghostarchive.org (Global: 32nd place; English: 21st place)