메뉴 건너뛰기




Volumn 3, Issue , 2003, Pages 1439-1461

Use of the zero-norm with linear models and kernel methods

Author keywords

[No Author keywords available]

Indexed keywords

KERNEL METHODS; MICROARRAY DATA; MULTI-CATEGORY CLASSIFICATION; PRACTICAL METHOD; SIMPLE MODIFICATIONS; TRAINING DATA; TRAINING ERRORS; VARIABLE AND FEATURE SELECTION;

EID: 84890520049     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (668)

References (32)
  • 1
    • 0000874557 scopus 로고
    • Theoretical foundations of the potential function method in pattern recognition learning
    • M. Aizerman, E. Braverman, and L. Rozonoer. Theoretical foundations of the potential function method in pattern recognition learning. Automation and Remote Control, 25:821 - 837, 1964.
    • (1964) Automation and Remote Control , vol.25 , pp. 821-837
    • Aizerman, M.1    Braverman, E.2    Rozonoer, L.3
  • 2
    • 0034598746 scopus 로고    scopus 로고
    • Distinct types of diffues large b-cell lymphoma identified by gene expression profiling
    • A.A. Alizadeh. Distinct types of diffues large b-cell lymphoma identified by gene expression profiling. Nature, 403:503-511, 2000.
    • (2000) Nature , vol.403 , pp. 503-511
    • Alizadeh, A.A.1
  • 3
    • 0033536012 scopus 로고    scopus 로고
    • Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon cancer tissues probed by oligonucleotide arrays
    • U. Alon, N. Barkai, D. Notterman, K. Gish, S. Ybarra, D. Mack, and A. Levine. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon cancer tissues probed by oligonucleotide arrays. Cell Biology, 96:6745-6750, 1999.
    • (1999) Cell Biology , vol.96 , pp. 6745-6750
    • Alon, U.1    Barkai, N.2    Notterman, D.3    Gish, K.4    Ybarra, S.5    Mack, D.6    Levine, A.7
  • 4
    • 0004493166 scopus 로고    scopus 로고
    • On the approximability of minimizing non zero variables or unsatisfied relations in linear systems
    • E. Amaldi and V. Kann. On the approximability of minimizing non zero variables or unsatisfied relations in linear systems. Theoretical Computer Science, 209:237-260, 1998.
    • (1998) Theoretical Computer Science , vol.209 , pp. 237-260
    • Amaldi, E.1    Kann, V.2
  • 5
    • 0026860799 scopus 로고
    • Robust linear programming discrimination of two linearly inseparable sets
    • K. P. Bennett and O. L. Mangasarian. Robust linear programming discrimination of two linearly inseparable sets. Optimization Methods and Software, 1:23-34, 1992.
    • (1992) Optimization Methods and Software , vol.1 , pp. 23-34
    • Bennett, K.P.1    Mangasarian, O.L.2
  • 6
    • 0031334221 scopus 로고    scopus 로고
    • Selection of relevant features and examples in machine learning
    • A. Blum and P. Langley. Selection of relevant features and examples in machine learning. Artificial Intelligence, 97:245-271, 1997.
    • (1997) Artificial Intelligence , vol.97 , pp. 245-271
    • Blum, A.1    Langley, P.2
  • 8
    • 0002709342 scopus 로고    scopus 로고
    • Feature selection via concave minimization and support vector machines
    • San Francisco, CA
    • P. S. Bradley and O. L. Mangasarian. Feature selection via concave minimization and support vector machines. In Proc. 13th ICML, pages 82-90, San Francisco, CA, 1998.
    • (1998) Proc. 13th ICML , pp. 82-90
    • Bradley, P.S.1    Mangasarian, O.L.2
  • 9
    • 0033721433 scopus 로고    scopus 로고
    • Massive data discrimination via linear support vector machines
    • P. S. Bradley and O. L. Mangasarian. Massive data discrimination via linear support vector machines. Optimization Methods and Software, 13(1):1-10, 2000. URL citeseer.nj.nec.com/bradley98massive.html.
    • (2000) Optimization Methods and Software , vol.13 , Issue.1 , pp. 1-10
    • Bradley, P.S.1    Mangasarian, O.L.2
  • 10
    • 0001010266 scopus 로고    scopus 로고
    • Feature selection via mathematical programming. Technical Report 95-21, Computer Sciences Department, University ofWisconsin, Madison,Wisconsin, 1995
    • P. S. Bradley, O. L. Mangasarian, and W. N. Street. Feature selection via mathematical programming. Technical Report 95-21, Computer Sciences Department, University ofWisconsin, Madison,Wisconsin, 1995. To appear in INFORMS Journal on Computing 10, 1998.
    • INFORMS Journal on Computing , vol.10 , pp. 1998
    • Bradley, P.S.1    Mangasarian, O.L.2    Street, W.N.3
  • 11
    • 34249753618 scopus 로고
    • Support vector networks
    • C. Cortes and V. Vapnik. Support vector networks. Machine Learning, 20:273 - 297, 1995.
    • (1995) Machine Learning , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 14
    • 0031624445 scopus 로고    scopus 로고
    • Large margin classification using the perceptron algorithm
    • Y. Freund and R. Schapire. Large margin classification using the perceptron algorithm. In COLT, 1998.
    • (1998) COLT
    • Freund, Y.1    Schapire, R.2
  • 16
    • 1542292950 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • I. Guyon, J. Weston, S. Barnhill, and V. Vapnik. Gene selection for cancer classification using support vector machines. Machine Learning, 2001.
    • (2001) Machine Learning
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 17
    • 0000963583 scopus 로고
    • Linear and nonlinear separation of patterns by linear programming
    • O.L. Mangasarian. Linear and nonlinear separation of patterns by linear programming. Operations Research, 13:444-452, 1965.
    • (1965) Operations Research , vol.13 , pp. 444-452
    • Mangasarian, O.L.1
  • 18
    • 55349084840 scopus 로고    scopus 로고
    • Inference for the generalization error
    • C. Nadeau and Y. Bengio. Inference for the generalization error. Machine Learning, 2001.
    • (2001) Machine Learning
    • Nadeau, C.1    Bengio, Y.2
  • 19
    • 0001854616 scopus 로고    scopus 로고
    • Assessing relevance determination methods using delve
    • R. M. Neal. Assessing relevance determination methods using delve. Neural Networks and Machine Learning, pages 97-129, 1998.
    • (1998) Neural Networks and Machine Learning , pp. 97-129
    • Neal, R.M.1
  • 23
    • 11144273669 scopus 로고
    • The perceptron: A probabilistic model for information storage and organization in the brain
    • F. Rosenblatt. The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review, 65(6):386-408, 1958.
    • (1958) Psychological Review , vol.65 , Issue.6 , pp. 386-408
    • Rosenblatt, F.1
  • 26
    • 0001224048 scopus 로고    scopus 로고
    • Sparse Bayesian learning and the relevance vector machine
    • M. E Tipping. Sparse Bayesian learning and the relevance vector machine. Journal of Machine Learning Research, 1:211-244, 2001.
    • (2001) Journal of Machine Learning Research , vol.1 , pp. 211-244
    • Tipping, M.E.1
  • 32
    • 0001254045 scopus 로고    scopus 로고
    • Multi-class support vector machines
    • M. Verleysen, editor, Brussels. D Facto
    • J. Weston and C. Watkins. Multi-class support vector machines. InM. Verleysen, editor, Proceedings ESANN, Brussels, 1999. D Facto.
    • (1999) Proceedings ESANN
    • Weston, J.1    Watkins, C.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.