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Volumn 1, Issue , 2015, Pages 78-86

A lower bound for the optimization of finite sums

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; NUMBER THEORY; NUMERICAL ANALYSIS;

EID: 84969540371     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (88)

References (15)
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    • 84873371070 scopus 로고    scopus 로고
    • Fast global convergence of gradient methods for high-dimensional statistical recovery
    • Agarwal, Alekh, Negahban, Sahand, and Wainwright, Martin J. Fast global convergence of gradient methods for high-dimensional statistical recovery. The Annals of Statistics, 40(5):2452-2482, 2012.
    • (2012) The Annals of Statistics , vol.40 , Issue.5 , pp. 2452-2482
    • Agarwal, A.1    Negahban, S.2    Wainwright, M.J.3
  • 3
    • 81155141540 scopus 로고    scopus 로고
    • Incremental gradient, subgradient, and proximal methods for convex optimization: A survey
    • Sra, S., Nowozin, S., and Wright, S. J. (eds.), MIT Press, 2012. Extended version: LIDS report LIDS-P2848, MIT
    • Bertsekas, Dimitri P. Incremental gradient, subgradient, and proximal methods for convex optimization: A survey. In Sra, S., Nowozin, S., and Wright, S. J. (eds.), Optimization for Machine Learning, pp. 85-119. MIT Press, 2012. Extended version: LIDS report LIDS-P2848, MIT, 2010.
    • (2010) Optimization for Machine Learning , pp. 85-119
    • Bertsekas, D.P.1
  • 4
    • 85162035281 scopus 로고    scopus 로고
    • The tradeoffs of large scale learning
    • Piatt, J.C., Koller, D., Singer, Y., and Roweis, S. (eds.). NIPS Foundation. URL http://Leon.bottou.org/papers/bottou-bousquet-2008
    • Bottou, Leon and Bousquet, Olivier. The tradeoffs of large scale learning. In Piatt, J.C., Koller, D., Singer, Y., and Roweis, S. (eds.), Advances in Neural Information Processing Systems, volume 20, pp. 161-168. NIPS Foundation (http://books.nips.cc), 2008. URL http://leon.bottou.org/papers/bottou-bousquet-2008.
    • (2008) Advances in Neural Information Processing Systems , vol.20 , pp. 161-168
    • Bottou, L.1    Bousquet, O.2
  • 6
    • 84898963415 scopus 로고    scopus 로고
    • Accelerating stochastic gradient descent using predictive variance reduction
    • Burges, C.J.C., Bottou, L., Welling. M., Ghahramani, Z., and Weinberger, K.Q. (eds.)
    • Johnson, Rie and Zhang, Tong. Accelerating stochastic gradient descent using predictive variance reduction. In Burges, C.J.C., Bottou, L., Welling. M., Ghahramani, Z., and Weinberger, K.Q. (eds.), Advances in Neural Information Processing Systems 26, pp. 315-323. 2013.
    • (2013) Advances in Neural Information Processing Systems , vol.26 , pp. 315-323
    • Johnson, R.1    Zhang, T.2
  • 7
    • 84877725219 scopus 로고    scopus 로고
    • A stochastic gradient method with an exponential convergence rate for finite training sets
    • Pereira, R, Burges, C.J.C., Bottou, L., and Weinberger, K.Q. (eds.)
    • Le Roux, Nicolas, Schmidt, Mark, and Bach, Francis. A stochastic gradient method with an exponential convergence rate for finite training sets. In Pereira, R, Burges, C.J.C., Bottou, L., and Weinberger, K.Q. (eds.), Advances in Neural Information Processing Systems 25, pp. 2663-2671. 2012.
    • (2012) Advances in Neural Information Processing Systems , vol.25 , pp. 2663-2671
    • Le Roux, N.1    Schmidt, M.2    Bach, F.3
  • 12
    • 84875134236 scopus 로고    scopus 로고
    • Stochastic dual coordinate ascent methods for regularized loss
    • Shalev-Shwartz, Shai and Zhang, Tong. Stochastic dual coordinate ascent methods for regularized loss. The Journal of Machine Learning Research, 14(1):567-599, 2013.
    • (2013) The Journal of Machine Learning Research , vol.14 , Issue.1 , pp. 567-599
    • Shalev-Shwartz, S.1    Zhang, T.2
  • 14
    • 84938533326 scopus 로고    scopus 로고
    • Introduction to the non-asymptotic analysis of random matrices
    • Eldar, Yonina C. and Kutyniok, Gitta (eds.). Cambridge University Press
    • Vershynin, Roman. Introduction to the non-asymptotic analysis of random matrices. In Eldar, Yonina C. and Kutyniok, Gitta (eds.). Compressed Sensing, pp. 210-268. Cambridge University Press, 2012.
    • (2012) Compressed Sensing , pp. 210-268
    • Vershynin, R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.