메뉴 건너뛰기




Volumn 1, Issue , 2012, Pages 28-36

Feature clustering for accelerating parallel coordinate descent

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMIC APPROACH; CONVERGENCE ANALYSIS; COORDINATE DESCENT; FEATURE CLUSTERING; HIGH-DIMENSIONAL; LOSS MINIMIZATION; PARALLEL COORDINATES; REGRESSION PROBLEM;

EID: 84877770112     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (49)

References (11)
  • 2
    • 84863879353 scopus 로고    scopus 로고
    • Coordinate descent algorithms for lasso penalized regression
    • T Wu and K Lange. Coordinate descent algorithms for lasso penalized regression. Annals of Applied Statistics, 2:224-244, 2008.
    • (2008) Annals of Applied Statistics , vol.2 , pp. 224-244
    • Wu, T.1    Lange, K.2
  • 6
    • 77956506829 scopus 로고    scopus 로고
    • 1 minimization with application to compressed sensing; a greedy algorithm solving the unconstrained problem
    • 1 Minimization with Application to Compressed Sensing; a Greedy Algorithm Solving the Unconstrained Problem. Inverse Problems and Imaging, 3:487-503, 2009.
    • (2009) Inverse Problems and Imaging , vol.3 , pp. 487-503
    • Li, Y.1    Osher, S.2
  • 9
    • 21844461582 scopus 로고    scopus 로고
    • A modified finite newton method for fast solution of large scale linear SVMs
    • S S Keerthi and D DeCoste. A modified finite Newton method for fast solution of large scale linear SVMs. Journal of Machine Learning Research, 6:341-361, 2005.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 341-361
    • Keerthi, S.S.1    DeCoste, D.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.