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Volumn 2, Issue , 2008, Pages 518-529

Active learning with model selection in linear regression

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATA MINING; ITERATIVE METHODS; NUMERICAL METHODS;

EID: 52649095948     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972788.47     Document Type: Conference Paper
Times cited : (21)

References (22)
  • 1
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • H. Akaike. A new look at the statistical model identification. IEEE Transactions on Automatic Control, AC-19(6):716-723, 1974.
    • (1974) IEEE Transactions on Automatic Control , vol.AC-19 , Issue.6 , pp. 716-723
    • Akaike, H.1
  • 2
    • 34248997891 scopus 로고    scopus 로고
    • Active learning for misspecified generalized linear models
    • B. Schölkopf, J. Platt, and T. Hoffman, editors, MIT Press, Cambridge, MA
    • F. Bach. Active learning for misspecified generalized linear models. In B. Schölkopf, J. Platt, and T. Hoffman, editors, Advances in Neural Information Processing Systems 19. MIT Press, Cambridge, MA, 2007.
    • (2007) Advances in Neural Information Processing Systems 19
    • Bach, F.1
  • 4
    • 34250263445 scopus 로고
    • Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
    • P. Craven and G. Wahba. Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation. Numerische Mathematik, 31:377-403, 1979.
    • (1979) Numerische Mathematik , vol.31 , pp. 377-403
    • Craven, P.1    Wahba, G.2
  • 6
    • 0033640737 scopus 로고    scopus 로고
    • Statistical active learning in multilayer perceptrons
    • K. Fukumizu. Statistical active learning in multilayer perceptrons. IEEE Transactions on Neural Networks, 11(1):17-26, 2000.
    • (2000) IEEE Transactions on Neural Networks , vol.11 , Issue.1 , pp. 17-26
    • Fukumizu, K.1
  • 9
    • 0038647337 scopus 로고    scopus 로고
    • Active learning algorithm using the maximum weighted log-likelihood estimator
    • T. Kanamori and H. Shimodaira. Active learning algorithm using the maximum weighted log-likelihood estimator. Journal of Statistical Planning and Inference, 116(1):149-162, 2003.
    • (2003) Journal of Statistical Planning and Inference , vol.116 , Issue.1 , pp. 149-162
    • Kanamori, T.1    Shimodaira, H.2
  • 10
    • 0001025418 scopus 로고
    • Bayesian interpolation
    • D. J. C. MacKay. Bayesian interpolation. Neural Computation, 4(3):415-447, 1992.
    • (1992) Neural Computation , vol.4 , Issue.3 , pp. 415-447
    • MacKay, D.J.C.1
  • 11
    • 0000695404 scopus 로고
    • Information-based objective functions for active data selection
    • D. J. C. MacKay. Information-based objective functions for active data selection. Neural Computation, 4(4):590-604, 1992.
    • (1992) Neural Computation , vol.4 , Issue.4 , pp. 590-604
    • MacKay, D.J.C.1
  • 14
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • J. Rissanen. Modeling by shortest data description. Automatica, 14(5):465-471, 1978.
    • (1978) Automatica , vol.14 , Issue.5 , pp. 465-471
    • Rissanen, J.1
  • 15
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • G. Schwarz. Estimating the dimension of a model. The Annals of Statistics, 6:461-464, 1978.
    • (1978) The Annals of Statistics , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 16
    • 0037527188 scopus 로고    scopus 로고
    • Improving predictive inference under covariate shift by weighting the log-likelihood function
    • H. Shimodaira. Improving predictive inference under covariate shift by weighting the log-likelihood function. Journal of Statistical Planning and Inference, 90(2):227-244, 2000.
    • (2000) Journal of Statistical Planning and Inference , vol.90 , Issue.2 , pp. 227-244
    • Shimodaira, H.1
  • 17
    • 30744458353 scopus 로고    scopus 로고
    • Active learning in approximately linear regression based on conditional expectation of generalization error
    • Jan
    • M. Sugiyama. Active learning in approximately linear regression based on conditional expectation of generalization error. Journal of Machine Learning Research, 7:141-166, Jan. 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 141-166
    • Sugiyama, M.1
  • 19
    • 34249027984 scopus 로고    scopus 로고
    • Input-dependent estimation of generalization error under covariate shift
    • M. Sugiyama and K.-R. Müller. Input-dependent estimation of generalization error under covariate shift. Statistics & Decisions, 23(4):249-279, 2005.
    • (2005) Statistics & Decisions , vol.23 , Issue.4 , pp. 249-279
    • Sugiyama, M.1    Müller, K.-R.2
  • 20
    • 0842310437 scopus 로고    scopus 로고
    • Active learning with model selection- Simultaneous optimization of sample points and models for trigonometric polynomial models
    • M. Sugiyama and H. Ogawa. Active learning with model selection- Simultaneous optimization of sample points and models for trigonometric polynomial models. IEICE Transactions on Information and Systems, E86-D( 12):2753-2763, 2003.
    • (2003) IEICE Transactions on Information and Systems , vol.E86-D , Issue.12 , pp. 2753-2763
    • Sugiyama, M.1    Ogawa, H.2
  • 21
    • 0012035667 scopus 로고    scopus 로고
    • Robust weights and designs for biased regression models: Least squares and generalized M-estimation
    • D. P. Wiens. Robust weights and designs for biased regression models: Least squares and generalized M-estimation. Journal of Statistical Planning and Inference, 83(2):395-412, 2000.
    • (2000) Journal of Statistical Planning and Inference , vol.83 , Issue.2 , pp. 395-412
    • Wiens, D.P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.