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Volumn , Issue , 2013, Pages

Better approximation and faster algorithm using the proximal average

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL CHALLENGES; CONVEX ANALYSIS; FUSED LASSOS; GRADIENT ALGORITHM; LARGE-SCALE MACHINE LEARNING; NUMERICAL EXPERIMENTS; OVERLAPPING GROUPS; SMOOTH FUNCTIONS;

EID: 84898962182     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (85)

References (20)
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    • Bach, F.1    Jenatton, R.2    Mairal, J.3    Obozinski, G.4
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    • The composite absolute penalties family for grouped and hierarchical variable selection
    • Peng Zhao, Guilherme Rocha, and Bin Yu. The composite absolute penalties family for grouped and hierarchical variable selection. Annals of Statistics, 37(6A):3468-3497, 2009.
    • (2009) Annals of Statistics , vol.37 , Issue.6 A , pp. 3468-3497
    • Zhao, P.1    Rocha, G.2    Yu, B.3
  • 6
    • 70149098541 scopus 로고    scopus 로고
    • Statistical estimation of correlated genome associations to a quantitative trait network
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    • Kim, S.1    Xing, E.P.2
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    • 17444406259 scopus 로고    scopus 로고
    • Smooth minimization of non-smooth functions
    • Yurii Nesterov. Smooth minimization of non-smooth functions. Mathematical Programming, 103(1):127-152, 2005.
    • (2005) Mathematical Programming , vol.103 , Issue.1 , pp. 127-152
    • Nesterov, Y.1
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    • 84886247153 scopus 로고    scopus 로고
    • Accelerated and inexact forward-backward algorithms
    • Silvia Villa, Saverio Salzo, Luca Baldassarre, and Alessandro Verri. Accelerated and inexact forward-backward algorithms. SIAM Journal on Optimization, 23(3):1607-1633, 2013.
    • (2013) SIAM Journal on Optimization , vol.23 , Issue.3 , pp. 1607-1633
    • Villa, S.1    Salzo, S.2    Baldassarre, L.3    Verri, A.4
  • 13
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    • Smoothing proximal gradient method for general structured sparse regression
    • Xi Chen, Qihan Lin, Seyoung Kim, Jaime G. Carbonell, and Eric P. Xing. Smoothing proximal gradient method for general structured sparse regression. The Annals of Applied Statistics, 6 (2):719-752, 2012.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.