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Volumn 1, Issue , 2016, Pages 620-629

Adaptive algorithms for online convex optimization with long-term constraints

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE ALGORITHMS; ARTIFICIAL INTELLIGENCE; CONVEX OPTIMIZATION; ECONOMIC AND SOCIAL EFFECTS; LEARNING SYSTEMS;

EID: 84997693812     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (62)

References (30)
  • 1
    • 84938271493 scopus 로고    scopus 로고
    • Fast algorithms for online stochastic convex programming
    • SIAM-Society for Industrial and Applied Mathematics
    • Agrawal, S. and Devanur, N. R. (2015). Fast algorithms for online stochastic convex programming. In SODA 2015 (ACM-SIAM Symposium on Discrete Algorithms). SIAM-Society for Industrial and Applied Mathematics.
    • (2015) SODA 2015 (ACM-SIAM Symposium on Discrete Algorithms)
    • Agrawal, S.1    Devanur, N.R.2
  • 10
    • 80052250414 scopus 로고    scopus 로고
    • Adaptive subgradient methods for online learning and stochastic optimization
    • Duchi, J., Hazan, E., and Singer, Y. (2011). Adaptive subgradient methods for online learning and stochastic optimization. Journal of Machine Learning Research, 12:2121-2159.
    • (2011) Journal of Machine Learning Research , vol.12 , pp. 2121-2159
    • Duchi, J.1    Hazan, E.2    Singer, Y.3
  • 12
    • 35348918820 scopus 로고    scopus 로고
    • Logarithmic regret algorithms for online convex optimization
    • Hazan, E., Agarwal, A., and Kale, S. (2007). Logarithmic regret algorithms for online convex optimization. Machine Learning, 69(2-3):169-192.
    • (2007) Machine Learning , vol.69 , Issue.2-3 , pp. 169-192
    • Hazan, E.1    Agarwal, A.2    Kale, S.3
  • 16
    • 0040165092 scopus 로고    scopus 로고
    • Practical aspects of the moreau-yosida regularization: Theoretical preliminaries
    • Lemaréchal, C. and Sagastizábal, C. (1997). Practical aspects of the moreau-yosida regularization: Theoretical preliminaries. SIAM Journal on Optimization, 7(2):367-385.
    • (1997) SIAM Journal on Optimization , vol.7 , Issue.2 , pp. 367-385
    • Lemaréchal, C.1    Sagastizábal, C.2
  • 17
    • 84869152925 scopus 로고    scopus 로고
    • Trading regret for efficiency: Online convex optimization with long term constraints
    • Mahdavi, M., Jin, R., and Yang, T. (2012a). Trading regret for efficiency: online convex optimization with long term constraints. Journal of Machine Learning Research, 13(1):2503-2528.
    • (2012) Journal of Machine Learning Research , vol.13 , Issue.1 , pp. 2503-2528
    • Mahdavi, M.1    Jin, R.2    Yang, T.3
  • 20
    • 33746094276 scopus 로고    scopus 로고
    • Online learning with constraints
    • Springer
    • Mannor, S. and Tsitsiklis, J. N. (2006). Online learning with constraints. In Learning Theory, pages 529-543. Springer.
    • (2006) Learning Theory , pp. 529-543
    • Mannor, S.1    Tsitsiklis, J.N.2
  • 22
    • 14944353419 scopus 로고    scopus 로고
    • Prox-method with rate of convergence o (1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convexconcave saddle point problems
    • Nemirovski, A. (2004). Prox-method with rate of convergence o (1/t) for variational inequalities with lipschitz continuous monotone operators and smooth convexconcave saddle point problems. SIAM Journal on Optimization, 15(1):229-251.
    • (2004) SIAM Journal on Optimization , vol.15 , Issue.1 , pp. 229-251
    • Nemirovski, A.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.