메뉴 건너뛰기




Volumn 40, Issue 6, 2011, Pages 1623-1646

Learning kernel-based halfspaces with the 0-1 loss

Author keywords

Kernel methods; Learning halfspaces; Learning theory

Indexed keywords

CRYPTOGRAPHIC ASSUMPTIONS; FINITE TIME; HALF SPACES; HALF-SPACE; HARDNESS RESULT; KERNEL METHODS; LEARNING THEORY; LIPSCHITZ CONSTANT; LOGISTIC REGRESSIONS; LOSS FUNCTIONS; TIME POLYNOMIALS;

EID: 84855575451     PISSN: 00975397     EISSN: None     Source Type: Journal    
DOI: 10.1137/100806126     Document Type: Conference Paper
Times cited : (49)

References (29)
  • 3
    • 84898957627 scopus 로고    scopus 로고
    • For valid generalization, the size of the weights is more important than the size of the network
    • MIT Press, Cambridge, MA
    • P. L. BARTLETT, For valid generalization, the size of the weights is more important than the size of the network, in Advances in Neural Information Processing Systems 9, MIT Press, Cambridge, MA, 1997, pp. 134-140.
    • (1997) Advances in Neural Information Processing Systems , vol.9 , pp. 134-140
    • Bartlett, P.L.1
  • 5
    • 0038453192 scopus 로고    scopus 로고
    • Rademacher and Gaussian complexities: Risk bounds and structural results
    • P. L. BARTLETT AND S. MENDELSON, Rademacher and Gaussian complexities: Risk bounds and structural results, J. Mach. Learn. Res., 3(2002), pp. 463-482.
    • (2002) J. Mach. Learn. Res. , vol.3 , pp. 463-482
    • Bartlett, P.L.1    Mendelson, S.2
  • 8
    • 78149346647 scopus 로고    scopus 로고
    • Polynomial regression under arbitrary product distributions
    • R. Servedio and T. Zhang, eds., Omnipress, Madison, WI
    • E. BLAIS, R. O'DONNELL, AND K. WIMMER, Polynomial regression under arbitrary product distributions, in Proceedings of the 21st Annual Conference on Learning Theory, R. Servedio and T. Zhang, eds., Omnipress, Madison, WI, 2008, pp. 193-204.
    • (2008) Proceedings of the 21st Annual Conference on Learning Theory , pp. 193-204
    • Blais, E.1    O'Donnell, R.2    Wimmer, K.3
  • 12
    • 84968502841 scopus 로고
    • The evaluation and estimation of the coefficients in the Chebyshev series expansion of a function
    • D. ELLIOT, The evaluation and estimation of the coefficients in the Chebyshev series expansion of a function, Math. Comp., 18(1964), pp. 274-284.
    • (1964) Math. Comp. , vol.18 , pp. 274-284
    • Elliot, D.1
  • 14
    • 35448964255 scopus 로고    scopus 로고
    • Hardness of learning halfspaces with noise
    • DOI 10.1109/FOCS.2006.33, 4031389, 47th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2006
    • V. GURUSWAMI AND P. RAGHAVENDRA, Hardness of learning halfspaces with noise, in Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS), IEEE Press, Piscataway, NJ, 2006, pp. 543-552. (Pubitemid 351175542)
    • (2006) Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS , pp. 543-552
    • Guruswami, V.1    Raghavendra, P.2
  • 15
    • 84855609314 scopus 로고    scopus 로고
    • On the complexity of linear prediction: Risk bounds, margin bounds, and regularization
    • MIT Press, Cambridge, MA
    • S. KAKADE, K. SRIDHARAN, AND A. TEWARI, On the complexity of linear prediction: Risk bounds, margin bounds, and regularization, in Advances in Neural Information Processing 21, MIT Press, Cambridge, MA, 2009, pp. 793-800.
    • (2009) Advances in Neural Information Processing , vol.21 , pp. 793-800
    • Kakade, S.1    Sridharan, K.2    Tewari, A.3
  • 17
  • 18
    • 35348921036 scopus 로고    scopus 로고
    • Cryptographic hardness for learning intersections of halfspaces
    • DOI 10.1109/FOCS.2006.24, 4031390, 47th Annual IEEE Symposium on Foundations of Computer Science, FOCS 2006
    • A. KLIVANS AND A. SHERSTOV, Cryptographic hardness for learning intersections of halfspaces, in Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science, IEEE Press, Piscataway, NJ, 2006, pp. 553-562. (Pubitemid 351175543)
    • (2006) Proceedings - Annual IEEE Symposium on Foundations of Computer Science, FOCS , pp. 553-562
    • Klivans, A.R.1    Sherstov, A.A.2
  • 22
    • 0025448521 scopus 로고
    • The strength of weak learnability
    • R. SCHAPIRE, The strength of weak learnability, Machine Learning, 5(1990), pp. 197-227.
    • (1990) Machine Learning , vol.5 , pp. 197-227
    • Schapire, R.1
  • 25
    • 34247197035 scopus 로고    scopus 로고
    • Fast rates for support vector machines using Gaussian kernels
    • I. STEINWART AND C. SCOVEL, Fast rates for support vector machines using Gaussian kernels, Ann. Statist., 35(2007), pp. 575-607.
    • (2007) Ann. Statist. , vol.35 , pp. 575-607
    • Steinwart, I.1    Scovel, C.2
  • 26
    • 3142725508 scopus 로고    scopus 로고
    • Optimal aggregation of classifiers in statistical learning
    • DOI 10.1214/aos/1079120131
    • A. TSYBAKOV, Optimal aggregation of classifiers in statistical learning, Ann. Statist., 32(2004), pp. 135-166. (Pubitemid 41449306)
    • (2004) Annals of Statistics , vol.32 , Issue.1 , pp. 135-166
    • Tsybakov, A.B.1
  • 28
    • 0003241881 scopus 로고
    • Spline models for observational data
    • SIAM, Philadelphia
    • G. WAHBA, Spline Models for Observational Data, CBMS-NSF Reg. Conf. Ser. Appl. Math. 59, SIAM, Philadelphia, 1990.
    • (1990) CBMS-NSF Reg. Conf. Ser. Appl. Math. , vol.59
    • Wahba, G.1
  • 29
    • 4644257995 scopus 로고    scopus 로고
    • Statistical behavior and consistency of classification methods based on convex risk minimization
    • T. ZHANG, Statistical behavior and consistency of classification methods based on convex risk minimization, Ann. Statist., 32(2004), pp. 56-85.
    • (2004) Ann. Statist. , vol.32 , pp. 56-85
    • Zhang, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.