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Volumn , Issue , 2014, Pages 8292-8296

A saddle point algorithm for networked online convex optimization

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CONVEX OPTIMIZATION; LAGRANGE MULTIPLIERS; OPTIMIZATION; SIGNAL PROCESSING;

EID: 84905252682     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2014.6855218     Document Type: Conference Paper
Times cited : (15)

References (13)
  • 1
    • 71149120542 scopus 로고    scopus 로고
    • Proximal regularization for online and batch learning
    • A. P. Danyluk, L. Bottou, and M. L. Littman, Eds., ACM.
    • C. B. Do, Q. V. Le, and C. Foo, "Proximal regularization for online and batch learning., " in ICML, A. P. Danyluk, L. Bottou, and M. L. Littman, Eds. 2009, vol. 382 of ACM International Conference Proceeding Series, p. 33, ACM.
    • (2009) ICML382 of ACM International Conference Proceeding Series , pp. 33
    • Do, C.B.1    Le, Q.V.2    Foo, C.3
  • 2
    • 70349668835 scopus 로고    scopus 로고
    • Approximate primal solutions and rate analysis for dual subgradient methods
    • A. Nedic and A. Ozdaglar, "Approximate primal solutions and rate analysis for dual subgradient methods, " SIAM Journal on Optimization, vol. 19, no. 4, pp. 1757-1780, 2008.
    • (2008) SIAM Journal on Optimization , vol.19 , Issue.4 , pp. 1757-1780
    • Nedic, A.1    Ozdaglar, A.2
  • 3
    • 84894665814 scopus 로고    scopus 로고
    • Dual averaging and proximal gradient descent for online alternating direction multiplier method
    • Atlanta, GA, JMLR Workshop and Conference Proceedings
    • T. Suzuki, "Dual averaging and proximal gradient descent for online alternating direction multiplier method, " in Proceedings of the 30th International Conference on Machine Learning (ICML-13), Atlanta, GA, vol. 28, pp. 392-400, JMLR Workshop and Conference Proceedings.
    • (2013) Proceedings of the 30th International Conference on Machine Learning (ICML-13) , vol.28 , pp. 392-400
    • Suzuki, T.1
  • 5
    • 78049361018 scopus 로고    scopus 로고
    • Distributed stochastic subgradient projection algorithms for convex optimization
    • S. S. Ram, A. Nedic, and V. V. Veeravalli, "Distributed stochastic subgradient projection algorithms for convex optimization, " Journal of Optimization Theory and Applications, vol. 147, no. 3, pp. 516-545, 2010.
    • (2010) Journal of Optimization Theory and Applications , vol.147 , Issue.3 , pp. 516-545
    • Ram, S.S.1    Nedic, A.2    Veeravalli, V.V.3
  • 6
    • 84859418371 scopus 로고    scopus 로고
    • Online learning and online convex optimization
    • Feb
    • S. Shalev-Shwartz, "Online learning and online convex optimization, " Found. Trends Mach. Learn., vol. 4, no. 2, pp. 107-194, Feb. 2012.
    • (2012) Found. Trends Mach. Learn. , vol.4 , Issue.2 , pp. 107-194
    • Shalev-Shwartz, S.1
  • 11
    • 70450145290 scopus 로고
    • Studies in linear and nonlinear programming
    • H. B. Chenery, S. M. Johnson, S. Karlin, T. Marschak, R. M. Solow. Stanford University Press, Stanford
    • K. J. Arrow, L. Hurwicz, and H. Uzawa, Studies in linear and nonlinear programming, With contributions by H. B. Chenery, S. M. Johnson, S. Karlin, T. Marschak, R. M. Solow. Stanford Mathematical Studies in the Social Sciences, vol. II. Stanford University Press, Stanford, 1958.
    • (1958) With Contributions by Stanford Mathematical Studies in the Social Sciences , vol.2
    • Arrow, K.J.1    Hurwicz, L.2    Uzawa, H.3
  • 12
    • 64549083384 scopus 로고    scopus 로고
    • Distributed subgradient methods for convex optimization
    • I. Lobel and A. Ozdaglar, "Distributed subgradient methods for convex optimization, " LIDS Report, vol. 2800, 2009.
    • (2009) LIDS Report 2800
    • Lobel, I.1    Ozdaglar, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.