메뉴 건너뛰기




Volumn , Issue , 2013, Pages

Linear convergence with condition number independent access of full gradients

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CONVEX OPTIMIZATION; NUMBER THEORY; OPTIMIZATION;

EID: 84898971059     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (149)

References (26)
  • 1
    • 84860244324 scopus 로고    scopus 로고
    • Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization
    • A. Agarwal, P. L. Bartlett, P. Ravikumar, and M. J. Wainwright. Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization. IEEE Transactions on Information Theory, 58(5):3235-3249, 2012.
    • (2012) IEEE Transactions on Information Theory , vol.58 , Issue.5 , pp. 3235-3249
    • Agarwal, A.1    Bartlett, P.L.2    Ravikumar, P.3    Wainwright, M.J.4
  • 2
    • 0031285678 scopus 로고    scopus 로고
    • A new class of incremental gradient methods for least squares problems
    • D. P. Bertsekas. A new class of incremental gradient methods for least squares problems. SIAM Journal on Optimization, 7(4):913-926, 1997.
    • (1997) SIAM Journal on Optimization , vol.7 , Issue.4 , pp. 913-926
    • Bertsekas, D.P.1
  • 6
    • 84871576447 scopus 로고    scopus 로고
    • Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization i: A generic algorithmic framework
    • S. Ghadimi and G. Lan. Optimal stochastic approximation algorithms for strongly convex stochastic composite optimization i: a generic algorithmic framework. SIAM Journal on Optimization, 22(4):1469-1492, 2012.
    • (2012) SIAM Journal on Optimization , vol.22 , Issue.4 , pp. 1469-1492
    • Ghadimi, S.1    Lan, G.2
  • 9
    • 84898471955 scopus 로고    scopus 로고
    • Beyond the regret minimization barrier: An optimal algorithm for stochastic strongly-convex optimization
    • E. Hazan and S. Kale. Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization. In Proceedings of the 24th Annual Conference on Learning Theory, pages 421-436, 2011.
    • (2011) Proceedings of the 24th Annual Conference on Learning Theory , pp. 421-436
    • Hazan, E.1    Kale, S.2
  • 11
    • 84862273593 scopus 로고    scopus 로고
    • An optimal method for stochastic composite optimization
    • G. Lan. An optimal method for stochastic composite optimization. Mathematical Programming, 133:365-397, 2012.
    • (2012) Mathematical Programming , vol.133 , pp. 365-397
    • Lan, G.1
  • 12
    • 84889875343 scopus 로고
    • On solutions of stochastic programming problems by descent procedures with stochastic and deterministic directions
    • K. Marti. On solutions of stochastic programming problems by descent procedures with stochastic and deterministic directions. Methods of Operations Research, 33:281-293, 1979.
    • (1979) Methods of Operations Research , vol.33 , pp. 281-293
    • Marti, K.1
  • 13
    • 84889804117 scopus 로고
    • Rates of convergence of semi-stochastic approximation procedures for solving stochastic optimization problems
    • K. Marti and E. Fuchs. Rates of convergence of semi-stochastic approximation procedures for solving stochastic optimization problems. Optimization, 17(2):243-265, 1986.
    • (1986) Optimization , vol.17 , Issue.2 , pp. 243-265
    • Marti, K.1    Fuchs, E.2
  • 14
    • 70450197241 scopus 로고    scopus 로고
    • Robust stochastic approximation approach to stochastic programming
    • A. Nemirovski, A. Juditsky, G. Lan, and A. Shapiro. Robust stochastic approximation approach to stochastic programming. SIAM Journal on Optimization, 19(4):1574-1609, 2009.
    • (2009) SIAM Journal on Optimization , vol.19 , Issue.4 , pp. 1574-1609
    • Nemirovski, A.1    Juditsky, A.2    Lan, G.3    Shapiro, A.4
  • 16
    • 34548480020 scopus 로고
    • A method for unconstrained convex minimization problem with the rate of convergence O(1/k2)
    • Y. Nesterov. A method for unconstrained convex minimization problem with the rate of convergence O(1/k2). Doklady AN SSSR (translated as Soviet. Math. Docl.), 269:543-547, 1983.
    • (1983) Doklady AN SSSR (Translated As Soviet. Math. Docl , vol.269 , pp. 543-547
    • Nesterov, Y.1
  • 18
    • 17444406259 scopus 로고    scopus 로고
    • Smooth minimization of non-smooth functions
    • Y. Nesterov. Smooth minimization of non-smooth functions. Mathematical Programming, 103(1):127-152, 2005.
    • (2005) Mathematical Programming , vol.103 , Issue.1 , pp. 127-152
    • Nesterov, Y.1
  • 19
    • 80055058907 scopus 로고    scopus 로고
    • Gradient methods for minimizing composite objective function
    • Y. Nesterov. Gradient methods for minimizing composite objective function. Core discussion papers, 2007.
    • (2007) Core Discussion Papers
    • Nesterov, Y.1
  • 22
    • 84877725219 scopus 로고    scopus 로고
    • A stochastic gradient method with an exponential convergence rate for finite training sets
    • N. L. Roux, M. Schmidt, and F. Bach. A stochastic gradient method with an exponential convergence rate for finite training sets. In Advances in Neural Information Processing Systems 25, pages 2672-2680, 2012.
    • (2012) Advances in Neural Information Processing Systems , vol.25 , pp. 2672-2680
    • Roux, N.L.1    Schmidt, M.2    Bach, F.3
  • 23
    • 84875134236 scopus 로고    scopus 로고
    • Stochastic dual coordinate ascent methods for regularized loss minimization
    • S. Shalev-Shwartz and T. Zhang. Stochastic dual coordinate ascent methods for regularized loss minimization. Journal of Machine Learning Research, 14:567-599, 2013.
    • (2013) Journal of Machine Learning Research , vol.14 , pp. 567-599
    • Shalev-Shwartz, S.1    Zhang, T.2
  • 25
    • 17444402055 scopus 로고    scopus 로고
    • Svm soft margin classifiers: Linear programming versus quadratic programming
    • Q.Wu and D.-X. Zhou. Svm soft margin classifiers: Linear programming versus quadratic programming. Neural Computation, 17(5):1160-1187, 2005.
    • (2005) Neural Computation , vol.17 , Issue.5 , pp. 1160-1187
    • Wu, Q.1    Zhou, D.-X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.