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Volumn 4, Issue January, 2014, Pages 3059-3067

An accelerated proximal coordinate gradient method

Author keywords

[No Author keywords available]

Indexed keywords

CONVEX OPTIMIZATION; FUNCTIONS; INFORMATION SCIENCE; OPTIMIZATION; STOCHASTIC SYSTEMS;

EID: 84937904560     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (140)

References (23)
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    • Coordinate descent method for large-scale l2-loss linear support vector machines
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    • Chang, K.-W.1    Hsieh, C.-J.2    Lin, C.-J.3
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    • Accelerating stochastic gradient descent using predictive variance reduction
    • R. Johnson and T. Zhang. Accelerating stochastic gradient descent using predictive variance reduction. In Advances in Neural Information Processing Systems 26, pages 315-323. 2013.
    • (2013) Advances in Neural Information Processing Systems , vol.26 , pp. 315-323
    • Johnson, R.1    Zhang, T.2
  • 9
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    • An accelerated proximal coordinate gradient method and its application to regularized empirical risk minimization
    • (arXiv: 1407.1296)
    • Q. Lin, Z. Lu, and L. Xiao. An accelerated proximal coordinate gradient method and its application to regularized empirical risk minimization. Technical Report MSR-TR-2014-94, Microsoft Research, 2014. (arXiv: 1407.1296).
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    • Lin, Q.1    Lu, Z.2    Xiao, L.3
  • 10
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    • On the complexity analysis of randomized block-coordinate descent methods
    • Accepted by Series A (arXiv: 1305.4723)
    • Z. Lu and L. Xiao. On the complexity analysis of randomized block-coordinate descent methods. Accepted by Mathematical Programming, Series A, 2014. (arXiv: 1305.4723).
    • (2014) Mathematical Programming
    • Lu, Z.1    Xiao, L.2
  • 11
    • 0026678659 scopus 로고    scopus 로고
    • On the convergence of the coordinate descent method for convex differentiable minimization
    • Z. Q. Luo and P. Tseng. On the convergence of the coordinate descent method for convex differentiable minimization. Journal of Optimization Theory & Applications, 72(1): 7-35, 2002.
    • (2002) Journal of Optimization Theory & Applications , vol.72 , Issue.1 , pp. 7-35
    • Luo, Z.Q.1    Tseng, P.2
  • 13
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    • Efficiency of coordinate descent methods on huge-scale optimization problems
    • Y. Nesterov. Efficiency of coordinate descent methods on huge-scale optimization problems. SIAM Journal on Optimization, 22(2): 341-362, 2012.
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    • Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
    • P. Richtárik and M. Takáč. Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function. Mathematical Programming, 144(1): 1-38, 2014.
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    • A stochastic gradient method with an exponential convergence rate for finite training sets
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.