메뉴 건너뛰기




Volumn , Issue , 2013, Pages 249-256

A fast parallel SGD for matrix factorization in shared memory systems

Author keywords

Matrix factorization; Parallel computing; Recommender system; Shared memory algorithm; Stochastic gradient descent

Indexed keywords

LOAD BALANCE; MATRIX FACTORIZATIONS; SEQUENTIAL APPROACH; SHARED MEMORY ALGORITHMS; SHARED MEMORY SYSTEM; STOCHASTIC GRADIENT DESCENT;

EID: 84887588556     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2507157.2507164     Document Type: Conference Paper
Times cited : (144)

References (15)
  • 6
    • 0001079593 scopus 로고
    • Stochastic estimation of the maximum of a regression function
    • J. Kiefer and J. Wolfowitz. Stochastic estimation of the maximum of a regression function. The Annals of Mathematical Statistics, 23(3):462-466, 1952.
    • (1952) The Annals of Mathematical Statistics , vol.23 , Issue.3 , pp. 462-466
    • Kiefer, J.1    Wolfowitz, J.2
  • 7
    • 85008044987 scopus 로고    scopus 로고
    • Matrix factorization techniques for recommender systems
    • Y. Koren, R. M. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. Computer, 42(8):30-37, 2009.
    • (2009) Computer , vol.42 , Issue.8 , pp. 30-37
    • Koren, Y.1    Bell, R.M.2    Volinsky, C.3
  • 8
    • 80052652249 scopus 로고    scopus 로고
    • Efficient large-scale distributed training of conditional maximum entropy models
    • Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors
    • G. Mann, R. McDonald, M. Mohri, N. Silberman, and D. Walker. Efficient large-scale distributed training of conditional maximum entropy models. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, and A. Culotta, editors, Advances in Neural Information Processing Systems 22, pages 1231-1239. 2009.
    • (2009) Advances in Neural Information Processing Systems , vol.22 , pp. 1231-1239
    • Mann, G.1    McDonald, R.2    Mohri, M.3    Silberman, N.4    Walker, D.5
  • 10
    • 85162467517 scopus 로고    scopus 로고
    • HOGWILD!: A lock-free approach to parallelizing stochastic gradient descent
    • J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K. Weinberger, editors
    • F. Niu, B. Recht, C. Ré, and S. J. Wright. HOGWILD!: A lock-free approach to parallelizing stochastic gradient descent. In J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K. Weinberger, editors, Advances in Neural Information Processing Systems 24, pages 693-701, 2011.
    • (2011) Advances in Neural Information Processing Systems , vol.24 , pp. 693-701
    • Niu, F.1    Recht, B.2    Ré, C.3    Wright, S.J.4
  • 15
    • 85161967549 scopus 로고    scopus 로고
    • Parallelized stochastic gradient descent
    • J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. Zemel, and A. Culotta, editors
    • M. Zinkevich, M. Weimer, A. Smola, and L. Li. Parallelized stochastic gradient descent. In J. Lafferty, C. K. I. Williams, J. Shawe-Taylor, R. Zemel, and A. Culotta, editors, Advances in Neural Information Processing Systems 23, pages 2595-2603. 2010.
    • (2010) Advances in Neural Information Processing Systems , vol.23 , pp. 2595-2603
    • Zinkevich, M.1    Weimer, M.2    Smola, A.3    Li, L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.