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Volumn , Issue PART 3, 2013, Pages 2059-2067

Mini-batch primal and dual methods for SVMs

Author keywords

[No Author keywords available]

Indexed keywords

STOCHASTIC SYSTEMS;

EID: 84897543082     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (105)

References (20)
  • 1
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    • Distributed delayed stochastic optimization
    • Agarwal, A. and Duchi, J. Distributed delayed stochastic optimization. In NIPS, 2011.
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    • Agarwal, A.1    Duchi, J.2
  • 2
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    • Parallel coordinate descent for l1-regularized loss minimization
    • Bradley, J.K., Kyrola, A., Bickson, D., and Guestrin, C. Parallel coordinate descent for l1-regularized loss minimization. In ICML, 2011.
    • (2011) ICML
    • Bradley, J.K.1    Kyrola, A.2    Bickson, D.3    Guestrin, C.4
  • 3
    • 85162498265 scopus 로고    scopus 로고
    • Better mini-batch algorithms via accelerated gradient methods
    • Cotter, A., Shamir, O., Srebro, N., and Sridharan, K. Better mini-batch algorithms via accelerated gradient methods. In NIPS, 2011.
    • (2011) NIPS
    • Cotter, A.1    Shamir, O.2    Srebro, N.3    Sridharan, K.4
  • 5
    • 84897524172 scopus 로고    scopus 로고
    • Randomized smoothing for (parallel) stochastic optimization
    • Duchi, John, Bartlett, Peter L., and Wainwright, Martin J. Randomized smoothing for (parallel) stochastic optimization. In ICML, 2012a.
    • (2012) ICML
    • Duchi, J.1    Bartlett, P.L.2    Wainwright, M.J.3
  • 6
    • 84865694209 scopus 로고    scopus 로고
    • Randomized smoothing for stochastic optimization
    • June
    • Duchi, John, Bartlett, Peter L., and Wainwright, Martin J. Randomized smoothing for stochastic optimization. SIAM Journal on Optimization, 22(2): 674-701, June 2012b.
    • (2012) SIAM Journal on Optimization , vol.22 , Issue.2 , pp. 674-701
    • Duchi, J.1    Bartlett, P.L.2    Wainwright, M.J.3
  • 9
    • 84888875306 scopus 로고    scopus 로고
    • Libsvm
    • Libsvm. Datasets. http://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/ binary.html.
    • Datasets
  • 10
    • 84865692149 scopus 로고    scopus 로고
    • Efficiency of coordinate descent methods on huge-scale optimization problems
    • Nesterov, Yu. Efficiency of coordinate descent methods on huge-scale optimization problems. SIAM J. Optimization, 22:341-362, 2012.
    • (2012) SIAM J. Optimization , vol.22 , pp. 341-362
    • Nesterov, Yu.1
  • 11
    • 85162467517 scopus 로고    scopus 로고
    • Hogwild: A lock-free approach to parallelizing stochastic gradient descent
    • Shawe-Taylor, J., Zemel, R.S., Bartlett, P., Pereira, F.C.N., and Weinberger, K.Q. (eds.)
    • Niu, F., Recht, B., Re, C., and Wright, S. Hogwild: A lock-free approach to parallelizing stochastic gradient descent. In Shawe-Taylor, J., Zemel, R.S., Bartlett, P., Pereira, F.C.N., and Weinberger, K.Q. (eds.), NIPS 24, pp. 693-701. 2011.
    • (2011) NIPS 24 , pp. 693-701
    • Niu, F.1    Recht, B.2    Re, C.3    Wright, S.4
  • 15
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    • Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function
    • doi: 10.1007/s10107-012-0614-z
    • Richtárik, P. and Takáč, M. Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function. Mathematical Programming, 2013. doi: 10.1007/s10107-012-0614-z.
    • (2013) Mathematical Programming
    • Richtárik, P.1    Takáč, M.2
  • 16
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    • Stochastic Methods for 11-regularized Loss Minimization
    • Shalev-Shwartz, S. and Tewari, A. Stochastic Methods for 11-regularized Loss Minimization. JMLR, 12: 1865-1892, 2011.
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    • Shalev-Shwartz, S.1    Tewari, A.2
  • 20
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    • Solving large scale linear prediction using stochastic gradient descent algorithms
    • Zhang, T. Solving large scale linear prediction using stochastic gradient descent algorithms. In ICML, 2004.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.