메뉴 건너뛰기




Volumn 473, Issue , 2013, Pages 4-28

Tighter PAC-Bayes bounds through distribution-dependent priors

Author keywords

Exponential weights algorithm; Localized bounds; PAC Bayes; Semi supervised learning; Statistical learning theory; SVM

Indexed keywords

LOCALIZED BOUNDS; PAC-BAYES; SEMI-SUPERVISED LEARNING; STATISTICAL LEARNING THEORY; SVM;

EID: 84873278768     PISSN: 03043975     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.tcs.2012.10.013     Document Type: Conference Paper
Times cited : (114)

References (31)
  • 3
    • 84972574511 scopus 로고
    • Weighted sums of certain dependent random variables
    • K. Azuma Weighted sums of certain dependent random variables Tohoku Mathematical Journal 68 1967 357 367
    • (1967) Tohoku Mathematical Journal , vol.68 , pp. 357-367
    • Azuma, K.1
  • 4
    • 77950343112 scopus 로고    scopus 로고
    • A discriminative model for semi-supervised learning
    • M. Balcan, and A. Blum A discriminative model for semi-supervised learning Journal of the ACM 57 3 2010
    • (2010) Journal of the ACM , vol.57 , Issue.3
    • Balcan, M.1    Blum, A.2
  • 5
    • 9444289383 scopus 로고    scopus 로고
    • Regularization and semi-supervised learning on large graphs
    • J. Shawe-Taylor, Y. Singer, Lecture Notes in Computer Science, vol. 3120 Springer
    • M. Belkin, I. Matveeva, and P. Niyogi Regularization and semi-supervised learning on large graphs J. Shawe-Taylor, Y. Singer, 17th Annual Conference on Learning Theory (COLT 2004) Lecture Notes in Computer Science, vol. 3120 2004 Springer pp. 624-638
    • (2004) 17th Annual Conference on Learning Theory (COLT 2004) , pp. 624-638
    • Belkin, M.1    Matveeva, I.2    Niyogi, P.3
  • 6
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
    • M. Belkin, P. Niyogi, and V. Sindhwani Manifold regularization: a geometric framework for learning from labeled and unlabeled examples Journal of Machine Learning Research 7 2006 2399 2434
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 7
    • 38049025143 scopus 로고    scopus 로고
    • Occam's hammer
    • N. H. Bshouty, C. Gentile, Lecture Notes in Computer Science Springer
    • G. Blanchard, and F. Fleuret Occam's hammer N. H. Bshouty, C. Gentile, 20th Annual Conference on Learning Theory (COLT 2007) Lecture Notes in Computer Science, vol. 4539 2007 Springer pp. 112-126
    • (2007) 20th Annual Conference on Learning Theory (COLT 2007) , vol.4539 , pp. 112-126
    • Blanchard, G.1    Fleuret, F.2
  • 10
    • 78049358617 scopus 로고    scopus 로고
    • PAC-Bayesian supervised classification: The thermodynamics of statistical learning
    • Institute of Mathematical Statistics
    • O. Catoni, 2007. PAC-Bayesian supervised classification: the thermodynamics of statistical learning, Monograph Series of the Institute of Mathematical Statistics. Institute of Mathematical Statistics.
    • (2007) Monograph Series of the Institute of Mathematical Statistics
    • Catoni, O.1
  • 19
    • 21844462365 scopus 로고    scopus 로고
    • Tutorial on practical prediction theory for classification
    • J. Langford Tutorial on practical prediction theory for classification Journal of Machine Learning Research 6 2005 273 306
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 273-306
    • Langford, J.1
  • 23
    • 77956898846 scopus 로고    scopus 로고
    • Chromatic PAC-Bayes bounds for non-iid data: Applications to ranking and stationary β-mixing processes
    • L. Ralaivola, M. Szafranski, and G. Stempfel Chromatic PAC-Bayes bounds for non-iid data: applications to ranking and stationary β-mixing processes Journal of Machine Learning Research 11 2010 1927 1956
    • (2010) Journal of Machine Learning Research , vol.11 , pp. 1927-1956
    • Ralaivola, L.1    Szafranski, M.2    Stempfel, G.3
  • 24
    • 0041464774 scopus 로고    scopus 로고
    • PAC-Bayesian generalisation error bounds for gaussian process classification
    • M. Seeger PAC-Bayesian generalisation error bounds for gaussian process classification Journal of Machine Learning Research 3 2002 233 269
    • (2002) Journal of Machine Learning Research , vol.3 , pp. 233-269
    • Seeger, M.1
  • 27
    • 31844440904 scopus 로고    scopus 로고
    • Beyond the point cloud: From transductive to semi-supervised learning
    • L. D. Raedt, S. Wrobel, ACM International Conference Proceeding Series ACM
    • V. Sindhwani, P. Niyogi, and M. Belkin Beyond the point cloud: from transductive to semi-supervised learning L. D. Raedt, S. Wrobel, Proceedings of the Twenty-Second International Conference on Machine Learning (ICML 2005) ACM International Conference Proceeding Series, vol. 119 2005 ACM pp. 824-831
    • (2005) Proceedings of the Twenty-Second International Conference on Machine Learning (ICML 2005) , vol.119 , pp. 824-831
    • Sindhwani, V.1    Niyogi, P.2    Belkin, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.