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Volumn 1, Issue , 2017, Pages 192-206

Input convex neural networks: Supplementary material

Author keywords

[No Author keywords available]

Indexed keywords

FUNCTIONS; IMAGE ENHANCEMENT; NEURAL NETWORKS; REINFORCEMENT LEARNING;

EID: 85048666489     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (26)

References (45)
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    • Nonmonotone spectral projected gradient methods on convex sets
    • Birgin, Ernesto G, Martínez, José Mario, and Raydan, Marcos. Nonmonotone spectral projected gradient methods on convex sets. SIAM Journal on Optimization, 10(4):1196-1211, 2000.
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    • Birgin, E.G.1    Martínez, J.M.2    Raydan, M.3
  • 8
    • 80051762104 scopus 로고    scopus 로고
    • Distributed optimization and statistical learning via the alternating direction method of multipliers
    • Boyd, Stephen, Parikh, Ncal, Chu, Eric, Pcleato, Borja, and Eckstein, Jonathan. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends® in Machine Learning, 3(1):1-122, 2011.
    • (2011) Foundations and Trends® in Machine Learning , vol.3 , Issue.1 , pp. 1-122
    • Boyd, S.1    Parikh, N.2    Chu, E.3    Pcleato, B.4    Eckstein, J.5
  • 12
    • 80052250414 scopus 로고    scopus 로고
    • Adaptive subgradient methods for online learning and stochastic optimization
    • Duchi, John, Hazan, Elad, and Singer, Yoram. Adaptive subgradient methods for online learning and stochastic optimization. The Journal of Machine Learning Research, 12:2121-2159, 2011.
    • (2011) The Journal of Machine Learning Research , vol.12 , pp. 2121-2159
    • Duchi, J.1    Hazan, E.2    Singer, Y.3
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    • 60549110283 scopus 로고    scopus 로고
    • Convex piecewise-linear fitting
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    • Magnani, A.1    Boyd, S.P.2
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    • 85048688297 scopus 로고    scopus 로고
    • Trelgol Publishing USA
    • Oliphant, Travis E. A guide to NumPy, volume 1. Trelgol Publishing USA, 2006.
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    • Oliphant, T.E.1
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    • Learning representations by back-propagating errors
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    • Bundle methods for machine learning
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.