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Volumn , Issue PART 1, 2013, Pages 579-587

Dynamical models and tracking regret in online convex programming

Author keywords

[No Author keywords available]

Indexed keywords

CONVEX OPTIMIZATION; LEARNING SYSTEMS;

EID: 84897553108     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (112)

References (27)
  • 3
    • 41549101939 scopus 로고    scopus 로고
    • Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data
    • Banerjee, O., El Ghaoui, L., and d'Aspremont, A. Model selection through sparse maximum likelihood estimation for multivariate Gaussian or binary data. J. Mach. Learn. Res., 9:485-516, 2008. (Pubitemid 351469014)
    • (2008) Journal of Machine Learning Research , vol.9 , pp. 485-516
    • Banerjee, O.1    El, G.L.2    D'Aspremont, A.3
  • 4
    • 0037403111 scopus 로고    scopus 로고
    • Mirror descent and nonlinear projected subgradient methods for convex programming
    • Beck, A. and Teboulle, M. Mirror descent and nonlinear projected subgradient methods for convex programming. Operations Research Letters, 31:167-175, 2003.
    • (2003) Operations Research Letters , vol.31 , pp. 167-175
    • Beck, A.1    Teboulle, M.2
  • 5
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • DOI 10.1162/089976603321780317
    • Belkin, M. and Niyogi, P. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput., 15(6):1373-1396, June 2003. (Pubitemid 37049796)
    • (2003) Neural Computation , vol.15 , Issue.6 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 6
    • 33745604236 scopus 로고    scopus 로고
    • Stable signal recovery from incomplete and inaccurate measurements
    • DOI 10.1002/cpa.20124
    • Candes, E., Romberg, J., and Tao, T. Stable signal recovery from incomplete and inaccurate measurements. Communications on Pure and Applied Mathematics, 59(8):1207-1223, 2006. (Pubitemid 43988295)
    • (2006) Communications on Pure and Applied Mathematics , vol.59 , Issue.8 , pp. 1207-1223
    • Candes, E.J.1    Romberg, J.K.2    Tao, T.3
  • 13
    • 0042496213 scopus 로고    scopus 로고
    • Tracking the Best Linear Predictor
    • DOI 10.1162/153244301753683726
    • Herbster, M. and Warmuth, M. K. Tracking the best linear predictor. Journal of Machine Learning Research, 35(3):281-309, 2001. (Pubitemid 33687205)
    • (2001) Journal of Machine Learning Research , vol.1 , Issue.4 , pp. 281-309
    • Herbster, M.1    Warmuth, M.K.2
  • 15
    • 64149115569 scopus 로고    scopus 로고
    • Sparse online learning via truncated gradient
    • Langford, J., Li, L., and Zhang, T. Sparse online learning via truncated gradient. J. Mach. Learn. Res., 10: 777-801, 2009.
    • (2009) J. Mach. Learn. Res. , vol.10 , pp. 777-801
    • Langford, J.1    Li, L.2    Zhang, T.3
  • 16
    • 35148838877 scopus 로고
    • The weighted majority algorithm
    • Littlestone, N. and Warmuth, M. K. The weighted majority algorithm. Inf. Comput., 108(2):212-261, 1994.
    • (1994) Inf. Comput. , vol.108 , Issue.2 , pp. 212-261
    • Littlestone, N.1    Warmuth, M.K.2
  • 22
    • 0035741510 scopus 로고    scopus 로고
    • The statistical evaluation of social network dynamics
    • Snijders, T. A. B. The statistical evaluation of social network dynamics. Sociological Methodology, 31(1): 361-395, 2001. (Pubitemid 33584803)
    • (2001) Sociological Methodology , vol.31 , Issue.1 , pp. 361-395
    • Snijders, T.A.B.1
  • 23
    • 0030084185 scopus 로고    scopus 로고
    • Robust discrete-time minimum-variance filtering
    • PII S1053587X96016313
    • Theodor, Y. and Shaked, U. Robust discrete-time minimum-variance filtering. IEEE Trans. Sig. Proc., 44(2):181-189, 1996. (Pubitemid 126776424)
    • (1996) IEEE Transactions on Signal Processing , vol.44 , Issue.2 , pp. 181-189
    • Theodor, Y.1    Shaked, U.2
  • 24
    • 77954588549 scopus 로고    scopus 로고
    • Modified-CS: Modifying compressive sensing for problems with partially known support
    • Vaswani, N. and Lu, W. Modified-CS: Modifying compressive sensing for problems with partially known support. IEEE Trans. Sig. Proc., 58:4595-4607, 2010.
    • (2010) IEEE Trans. Sig. Proc. , vol.58 , pp. 4595-4607
    • Vaswani, N.1    Lu, W.2
  • 25
    • 78649396336 scopus 로고    scopus 로고
    • Dual averaging methods for regularized stochastic learning and online optimization
    • Xiao, L. Dual averaging methods for regularized stochastic learning and online optimization. J. Mach. Learn. Res., 11:2543-2596, 2010.
    • (2010) J. Mach. Learn. Res. , vol.11 , pp. 2543-2596
    • Xiao, L.1
  • 26
    • 0028448672 scopus 로고
    • Robust Kalman filtering for uncertain discrete-time systems
    • Xie, L., Soh, Y. C., and de Souza, C. E. Robust Kalman filtering for uncertain discrete-time systems. IEEE Trans. Autom. Control, 39:1310-1314, 1994.
    • (1994) IEEE Trans. Autom. Control , vol.39 , pp. 1310-1314
    • Xie, L.1    Soh, Y.C.2    De Souza, C.E.3
  • 27
    • 1942484421 scopus 로고    scopus 로고
    • Online convex programming and generalized infinitesimal gradient descent
    • Zinkevich, M. Online convex programming and generalized infinitesimal gradient descent. In Proc. Int. Conf. on Machine Learning (ICML), pp. 928-936, 2003.
    • (2003) Proc. Int. Conf. on Machine Learning (ICML) , pp. 928-936
    • Zinkevich, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.