메뉴 건너뛰기




Volumn 58, Issue 2, 2014, Pages 409-421

A unified algorithm for mixed l2,p-minimizations and its application in feature selection

Author keywords

Gradient projection; Mixed matrix norm; Non Lipschitz continuous; Unified algorithm

Indexed keywords

BIOINFORMATICS; OPTIMIZATION; PATTERN RECOGNITION;

EID: 84901189483     PISSN: 09266003     EISSN: 15732894     Source Type: Journal    
DOI: 10.1007/s10589-014-9648-x     Document Type: Article
Times cited : (45)

References (14)
  • 2
    • 57349174008 scopus 로고    scopus 로고
    • Enhancing sparsity by reweighed l 1 minimization
    • 1176.94014 2461611
    • Candès, Emmanuel J., Wakin, Michael B., Boyd, Stephen P.: Enhancing sparsity by reweighed l 1 minimization. J. Fourier Anal. Appl. 14(5), 877-905 (2008)
    • (2008) J. Fourier Anal. Appl. , vol.14 , Issue.5 , pp. 877-905
    • Candès, E.J.1    Wakin, M.B.2    Boyd, S.P.3
  • 3
    • 34548724437 scopus 로고    scopus 로고
    • Exact reconstructions of sparse signals via nonconvex minimization
    • 10.1109/LSP.2007.898300
    • Chartrand, R.: Exact reconstructions of sparse signals via nonconvex minimization. IEEE Signal Process. Lett. 14(10), 707-710 (2007)
    • (2007) IEEE Signal Process. Lett. , vol.14 , Issue.10 , pp. 707-710
    • Chartrand, R.1
  • 5
    • 78149326445 scopus 로고    scopus 로고
    • Lower bound theory of nonzero entries in solutions of l 2 - L p minimization
    • 10.1137/090761471 1242.90174 2735983
    • Chen, X.J., Xu, F.M., Ye, Y.Y.: Lower bound theory of nonzero entries in solutions of l 2 - l p minimization. SIAM J. Sci. Comput. 32(5), 2832-2852 (2010)
    • (2010) SIAM J. Sci. Comput. , vol.32 , Issue.5 , pp. 2832-2852
    • Chen, X.J.1    Xu, F.M.2    Ye, Y.Y.3
  • 7
    • 0036489046 scopus 로고    scopus 로고
    • Comparison of discrimination methods for the classification of tumors using gene expression data
    • 10.1198/016214502753479248 1073.62576
    • Dudoit, S., Fridly, J., Speed, T.P.: Comparison of discrimination methods for the classification of tumors using gene expression data. J. Am. Stat. Assoc. 97(457), 77-87 (2002)
    • (2002) J. Am. Stat. Assoc. , vol.97 , Issue.457 , pp. 77-87
    • Dudoit, S.1    Fridly, J.2    Speed, T.P.3
  • 9
  • 10
    • 0036735386 scopus 로고    scopus 로고
    • Translation of microarray data into clinically relevant cancer diagnoistic tests using gene expression ratios in lung cancer and mesothelioma
    • Gordon, G.J., Jensen, R.V., Hsiao, L.L., Gullans, S.R., Blumenstock, J.E., Ramaswamy, S., Richards, W.G., Sugarbaker, D.J., Bueno, R.: Translation of microarray data into clinically relevant cancer diagnoistic tests using gene expression ratios in lung cancer and mesothelioma. Cancer Res. 62(17), 4963-4967 (2002)
    • (2002) Cancer Res. , vol.62 , Issue.17 , pp. 4963-4967
    • Gordon, G.J.1    Jensen, R.V.2    Hsiao, L.L.3    Gullans, S.R.4    Blumenstock, J.E.5    Ramaswamy, S.6    Richards, W.G.7    Sugarbaker, D.J.8    Bueno, R.9
  • 13
    • 80051543708 scopus 로고    scopus 로고
    • L p - L q Penalty for sparse linear and sparse multiple kernel multitask learning
    • 10.1109/TNN.2011.2157521
    • Rakotomamonjy, A., Flamary, R., Gasso, G., Canu, S.: l p - l q Penalty for sparse linear and sparse multiple kernel multitask learning. IEEE Transac. Neural Netw. 22(8), 1307-1320 (2011)
    • (2011) IEEE Transac. Neural Netw. , vol.22 , Issue.8 , pp. 1307-1320
    • Rakotomamonjy, A.1    Flamary, R.2    Gasso, G.3    Canu, S.4
  • 14
    • 0000788854 scopus 로고
    • The gradient projection method for nonlinear programming. Part 1 Linear constraints
    • 0099.36405
    • Rosen, J.B.: The gradient projection method for nonlinear programming. Part 1 Linear constraints. J. SIAM 8, 181-217 (1960)
    • (1960) J. SIAM , vol.8 , pp. 181-217
    • Rosen, J.B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.