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Volumn 22, Issue , 2012, Pages 282-290

Protocols for learning classifiers on distributed data

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE;

EID: 84954221698     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (16)

References (20)
  • 1
    • 84954269292 scopus 로고    scopus 로고
    • http://metaoptimize.com/qa/questions/1885/supposeyour-training-and-test-set-are-generated-by-a-cunningadversary, 2010.
    • (2010)
  • 3
    • 0032645080 scopus 로고    scopus 로고
    • An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
    • Eric Bauer and Ron Kohavi. An empirical comparison of voting classification algorithms: Bagging, boosting, and variants. Machine Learning, 36(1-2), 1999.
    • (1999) Machine Learning , vol.36 , Issue.1-2
    • Bauer, E.1    Kohavi, R.2
  • 5
    • 71149102767 scopus 로고    scopus 로고
    • Robust bounds for classification via selective sampling
    • Montreal, Canada
    • Nicolo Cesa-Bianchi, Claudio Gentile, and Francesco Orabona. Robust bounds for classification via selective sampling. In ICML, Montreal, Canada, 2009.
    • (2009) ICML
    • Cesa-Bianchi, N.1    Gentile, C.2    Orabona, F.3
  • 6
    • 85127836544 scopus 로고    scopus 로고
    • Discriminative training methods for hidden markov models: Theory and experiments with per-ceptron algorithms
    • Stroudsburg, USA
    • Michael Collins. Discriminative training methods for hidden markov models: theory and experiments with per-ceptron algorithms. In EMNLP, Stroudsburg, USA, 2002.
    • (2002) EMNLP
    • Collins, M.1
  • 7
    • 84875634609 scopus 로고    scopus 로고
    • Robust selective sampling from single and multiple teachers
    • Haifa, Israel
    • Ofer Dekel, Claudio Gentile, and Karthik Sridharan. Robust selective sampling from single and multiple teachers. In COLT, Haifa, Israel, 2010.
    • (2010) COLT
    • Dekel, O.1    Gentile, C.2    Sridharan, K.3
  • 8
    • 0029521676 scopus 로고
    • Sample compression, learnability, and the vapnik-chervonenkis dimension
    • Sally Floyd and Manfred Warmuth. Sample compression, learnability, and the vapnik-chervonenkis dimension. Machine Learning, 50:269-304, 1995.
    • (1995) Machine Learning , vol.50 , pp. 269-304
    • Floyd, S.1    Warmuth, M.2
  • 14
    • 78049528115 scopus 로고    scopus 로고
    • Machine learning in adversarial environments
    • Pavel Laskov and Richard Lippmann. Machine learning in adversarial environments. Machine Learning, 81(2), 2010.
    • (2010) Machine Learning , vol.81 , pp. 2
    • Laskov, P.1    Lippmann, R.2
  • 15
    • 0035789273 scopus 로고    scopus 로고
    • The distributed boosting algorithm
    • San Francisco, USA
    • Aleksandar Lazarevic and Zoran Obradovic. The distributed boosting algorithm. In KDD, San Francisco, USA, 2001.
    • (2001) KDD
    • Lazarevic, A.1    Obradovic, Z.2
  • 16
    • 80052652249 scopus 로고    scopus 로고
    • Efficient large-scale distributed training of conditional maximum entropy models
    • Vancouver, Canada
    • Gideon Mann, Ryan McDonald, Mehryar Mohri, Nathan Silberman, and Dan Walker. Efficient large-scale distributed training of conditional maximum entropy models. In NIPS, Vancouver, Canada, 2009.
    • (2009) NIPS
    • Mann, G.1    McDonald, R.2    Mohri, M.3    Silberman, N.4    Walker, D.5
  • 17
    • 80052650170 scopus 로고    scopus 로고
    • Distributed training strategies for the structured perceptron
    • Los Angeles, California
    • Ryan McDonald, Keith Hall, and Gideon Mann. Distributed training strategies for the structured perceptron. In NAACL HLT, Los Angeles, California, 2010.
    • (2010) NAACL HLT
    • McDonald, R.1    Hall, K.2    Mann, G.3
  • 19
    • 68949137209 scopus 로고    scopus 로고
    • Active learning literature survey
    • University of Wisconsin-Madison
    • Burr Settles. Active learning literature survey. In Computer Sciences Technical Report 1648, University of Wisconsin-Madison, 2009.
    • (2009) Computer Sciences Technical Report , vol.1648
    • Settles, B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.