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Volumn , Issue , 2009, Pages 844-852

On the algorithmics and applications of a mixed-norm based kernel learning formulation

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMICS; COMPONENT LEVELS; KERNEL LEARNING; LEARNING FORMULATION; MIXED-NORM; MULTIPLE KERNEL LEARNING; NONCONVEX PROBLEM; OBJECT CATEGORIZATION; REAL-WORLD PROBLEM; REGULARISATION;

EID: 77956529614     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (30)

References (20)
  • 2
    • 0037403111 scopus 로고    scopus 로고
    • Mirror descent and nonlinear projected subgradient methods for convex optimization
    • Amir Beck and Marc Teboulle. Mirror descent and nonlinear projected subgradient methods for convex optimization. Operations Research Letters, 31:167-175, 2003.
    • (2003) Operations Research Letters , vol.31 , pp. 167-175
    • Beck, A.1    Teboulle, M.2
  • 3
    • 0036342276 scopus 로고    scopus 로고
    • The ordered subsets mirror descent optimization method with applications to tomography
    • Aharon Ben-Tal, Tamar Margalit, and Arkadi Nemirovski. The Ordered Subsets Mirror Descent Optimization Method with Applications to Tomography. SIAM Journal of Optimization, 12(1):79-108, 2001.
    • (2001) SIAM Journal of Optimization , vol.12 , Issue.1 , pp. 79-108
    • Ben-Tal, A.1    Margalit, T.2    Nemirovski, A.3
  • 4
    • 17444361978 scopus 로고    scopus 로고
    • Non-euclidean restricted memory level method for large-scale convex optimization
    • Aharon Ben-Tal and Arkadi Nemirovski. Non-euclidean Restricted Memory Level Method for Large-scale Convex Optimization. Mathematical Programming, 102(3):407-456, 2005.
    • (2005) Mathematical Programming , vol.102 , Issue.3 , pp. 407-456
    • Ben-Tal, A.1    Nemirovski, A.2
  • 7
    • 84932617705 scopus 로고    scopus 로고
    • Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories
    • R. Fergus L. Fei-Fei and P. Perona. Learning generative visual models from few training examples: an incremental bayesian approach tested on 101 object categories. In IEEE. CVPR 2004, Workshop on Generative-Model Based Vision., 2004.
    • (2004) IEEE. CVPR 2004, Workshop on Generative-model Based Vision
    • Fergus, R.1    Fei-Fei, L.2    Perona, P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.