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Volumn 33, Issue , 2014, Pages 531-539

Fugue: Slow-worker-agnostic distributed learning for big models on big data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA HANDLING; LEARNING SYSTEMS;

EID: 84955497549     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (14)

References (19)
  • 2
    • 84858012279 scopus 로고    scopus 로고
    • Scalable inference in latent variable models
    • Amr Ahmed, Moahmed Aly, Joseph Gonzalez, Shravan Narayanamurthy, and Alexander J. Smola. Scalable inference in latent variable models. In WSDM, pages 123-132, 2012.
    • (2012) WSDM , pp. 123-132
    • Ahmed, A.1    Aly, M.2    Gonzalez, J.3    Narayanamurthy, S.4    Smola, A.J.5
  • 15
    • 84863735533 scopus 로고    scopus 로고
    • Distributed GraphLab: A framework for machine learning and data mining in the cloud
    • Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin, and Joseph M. Hellerstein. Distributed GraphLab: A Framework for Machine Learning and Data Mining in the Cloud. PVLDB, 2012.
    • (2012) PVLDB
    • Low, Y.1    Gonzalez, J.2    Kyrola, A.3    Bickson, D.4    Guestrin, C.5    Hellerstein, J.M.6
  • 17
    • 85162467517 scopus 로고    scopus 로고
    • Hogwild!: A lock-free approach to parallelizing stochastic gradient descent
    • Feng Niu, Benjamin Recht, Christopher Ré, and Stephen J Wright. Hogwild!: A lock-free approach to parallelizing stochastic gradient descent. In NIPS, 2011.
    • (2011) NIPS
    • Niu, F.1    Recht, B.2    Ré, C.3    Wright, S.J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.