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Volumn , Issue , 2013, Pages 37-47

Distributed large-scale natural graph factorization

Author keywords

Asynchronous algorithms; Distributed optimization; Graph algorithms; Graph factorization; Graph partitioning; Large scale machine learning; Matrix factorization

Indexed keywords

ELECTRONIC MAIL; FACTORIZATION; GRAPHIC METHODS; MACHINE LEARNING; WORLD WIDE WEB;

EID: 84893071858     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2488388.2488393     Document Type: Conference Paper
Times cited : (694)

References (26)
  • 2
    • 80052659792 scopus 로고    scopus 로고
    • Scalable distributed inference of dynamic user interests for behavioral targeting
    • A. Ahmed, Y Low, M. Aly, V. Josifovski, and A. Smola. Scalable Distributed Inference of Dynamic User Interests for Behavioral Targeting. In KDD, 2011.
    • (2011) KDD
    • Ahmed, A.1    Low, Y.2    Aly, M.3    Josifovski, V.4    Smola, A.5
  • 3
    • 0001090598 scopus 로고
    • Representations for partially exchangeable arrays of random variables
    • D. Aldous. Representations for partially exchangeable arrays of random variables. Journal of Multivariate Analysis, 11(4):581-598, 1981.
    • (1981) Journal of Multivariate Analysis , vol.11 , Issue.4 , pp. 581-598
    • Aldous, D.1
  • 4
    • 84858010856 scopus 로고    scopus 로고
    • Overlapping clusters for distributed computation
    • R. Andersen, D. Gleich, and V. Mirrokni. Overlapping clusters for distributed computation. In WSDM, 2012.
    • (2012) WSDM
    • Andersen, R.1    Gleich, D.2    Mirrokni, V.3
  • 7
    • 0003713964 scopus 로고    scopus 로고
    • Athena Scientific, Belmont MA second edition
    • D. P. Bertsekas. Nonlinear Programming. Athena Scientific, Belmont, MA, second edition, 1999.
    • (1999) Nonlinear Programming
    • Bertsekas, D.P.1
  • 8
    • 0141607824 scopus 로고    scopus 로고
    • Latent Dirichlet allocation
    • D. Blei, A. Ng, and M. Jordan. Latent Dirichlet allocation. JMLR, 3:993-1022, 2003.
    • (2003) JMLR , vol.3 , pp. 993-1022
    • Blei, D.1    Ng, A.2    Jordan, M.3
  • 9
    • 80051762104 scopus 로고    scopus 로고
    • Distributed optimization and statistical learning via the alternating direction method of multipliers
    • S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends in Machine Learning, 3(1):1-123, 2010.
    • (2010) Foundations and Trends in Machine Learning , vol.3 , Issue.1 , pp. 1-123
    • Boyd, S.1    Parikh, N.2    Chu, E.3    Peleato, B.4    Eckstein, J.5
  • 10
    • 0036040277 scopus 로고    scopus 로고
    • Similarity estimation techniques from rounding algorithms
    • M. Charikar. Similarity estimation techniques from rounding algorithms. In ACM Tymposium on Theory of Computing, pages 380-388, 2002.
    • (2002) ACM Tymposium on Theory of Computing , pp. 380-388
    • Charikar, M.1
  • 11
    • 80052668032 scopus 로고    scopus 로고
    • Large-scale matrix factorization with distributed stochastic gradient descent
    • R. Gemulla, E. Nijkamp, P. J. Haas, and Y. Sismanis. Large-scale matrix factorization with distributed stochastic gradient descent. In KDD, 69-77, 2011.
    • (2011) KDD , pp. 69-77
    • Gemulla, R.1    Nijkamp, E.2    Haas, P.J.3    Sismanis, Y.4
  • 13
    • 84864043341 scopus 로고    scopus 로고
    • Infinite latent feature models and the Indian Buffet Process
    • T. Grifiths and Z. Ghahramani. Infinite latent feature models and the Indian Buffet Process. NIPS 18, 475-482, 2006.
    • (2006) NIPS , vol.18 , pp. 475-482
    • Grifiths, T.1    Ghahramani, Z.2
  • 16
    • 85008044987 scopus 로고    scopus 로고
    • Matrix factorization techniques for recommender systems
    • Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. IEEE Computer, 42(8):30-37, 2009.
    • (2009) IEEE Computer , vol.42 , Issue.8 , pp. 30-37
    • Koren, Y.1    Bell, R.2    Volinsky, C.3
  • 17
    • 77954604765 scopus 로고    scopus 로고
    • Distributed nonnegative matrix factorization for web-scale dyadic data analysis on mapreduce
    • C. Liu, H.-C. Yang, J. Fan, L.-W. He, and Y.-M. Wang. Distributed nonnegative matrix factorization for web-scale dyadic data analysis on mapreduce. In WWW, 681-690, 2010.
    • (2010) WWW , pp. 681-690
    • Liu, C.1    Yang, H.-C.2    Fan, J.3    He, L.-W.4    Wang, Y.-M.5
  • 22
    • 85162467517 scopus 로고    scopus 로고
    • Hogwild: A lock-free approach to parallelizing stochastic gradient descent
    • B. Recht, C. Re, S. Wright, and F. Niu. Hogwild: A lock-free approach to parallelizing stochastic gradient descent. In NIPS, pages 693-701, 2011.
    • (2011) NIPS , pp. 693-701
    • Recht, B.1    Re, C.2    Wright, S.3    Niu, F.4
  • 23
    • 80052119994 scopus 로고    scopus 로고
    • An architecture for parallel topic models
    • A. J. Smola and S. Narayanamurthy. An architecture for parallel topic models. In VLDB, 2010.
    • (2010) VLDB
    • Smola, A.J.1    Narayanamurthy, S.2
  • 24
    • 80052672399 scopus 로고    scopus 로고
    • Counting triangles and the curse of the last reducer
    • S. Suri and S. Vassilvitskii. Counting triangles and the curse of the last reducer. In WWW, 607-614. 2011.
    • (2011) WWW , pp. 607-614
    • Suri, S.1    Vassilvitskii, S.2
  • 25
    • 72449152230 scopus 로고    scopus 로고
    • Fast nonparametric matrix factorization for large-scale collaborative filtering
    • K. Yu, S. Zhu, J. Lafferty, and Y. Gong. Fast nonparametric matrix factorization for large-scale collaborative filtering. In SIGIR, pages 211-218, 2009.
    • (2009) SIGIR , pp. 211-218
    • Yu, K.1    Zhu, S.2    Lafferty, J.3    Gong, Y.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.