메뉴 건너뛰기




Volumn 34, Issue 3, 2011, Pages 229-240

Multiple-view multiple-learner semi-supervised learning

Author keywords

Ensemble learning; Multiple viewlearning; Neural network; Semi supervised Learning

Indexed keywords

CO-TRAINING; DATA SETS; ENSEMBLE LEARNING; ENSEMBLE OF CLASSIFIERS; INDUCTIVE LEARNING; KNOWLEDGE IT; LABELED AND UNLABELED DATA; LABELED DATA; LEARNING PARADIGMS; MULTIPLE VIEWS; MULTIPLE-VIEW; MULTIPLE-VIEWLEARNING; SEMI-SUPERVISED LEARNING; SEMI-SUPERVISED LEARNING METHODS; UNLABELED DATA;

EID: 84855519943     PISSN: 13704621     EISSN: 1573773X     Source Type: Journal    
DOI: 10.1007/s11063-011-9195-8     Document Type: Review
Times cited : (52)

References (24)
  • 1
    • 84898930761 scopus 로고    scopus 로고
    • Co-training and expansion: Towards bridging theory and practice
    • Balcan M, Blum A, Yang K (2005) Co-training and expansion: towards bridging theory and practice. Adv Neural Inf Process Syst 17:89-96
    • (2005) Adv Neural Inf Process Syst , vol.17 , pp. 89-96
    • Balcan, M.1    Blum, A.2    Yang, K.3
  • 3
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L (1996) Bagging predictors. Mach Learn 24:123-140 (Pubitemid 126724382)
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 4
    • 0031189914 scopus 로고    scopus 로고
    • Multitask learning
    • Caruana R (1997) Multitask learning. Mach Learn 28:41-75 (Pubitemid 127507169)
    • (1997) Machine Learning , vol.28 , Issue.1 , pp. 41-75
    • Caruana, R.1
  • 8
    • 0037403516 scopus 로고    scopus 로고
    • Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy
    • Kuncheva L, Whitaker C (2003) Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy. Mach Learn 51:181-207
    • (2003) Mach Learn , vol.51 , pp. 181-207
    • Kuncheva, L.1    Whitaker, C.2
  • 13
    • 84948481845 scopus 로고
    • An algorithm for suffix stripping
    • Porter MF (1980) An algorithm for suffix stripping. Program 14:130-137
    • (1980) Program , vol.14 , pp. 130-137
    • Porter, M.F.1
  • 14
    • 45549117987 scopus 로고
    • Term-weighting approaches in automatic text retrieval
    • Salton G, Buckley C (1988) Term-weighting approaches in automatic text retrieval. Inf Process Manag 24:513-523
    • (1988) Inf Process Manag , vol.24 , pp. 513-523
    • Salton, G.1    Buckley, C.2
  • 17
    • 79957848621 scopus 로고    scopus 로고
    • View construction for multi-view semi-supervised learning
    • Sun S, Jin F, Tu W (2011) View construction for multi-view semi-supervised learning. Lecture Notes in Computer Science 6675:595-601
    • (2011) Lecture Notes in Computer Science , vol.6675 , pp. 595-601
    • Sun, S.1    Jin, F.2    Tu, W.3
  • 18
    • 34548688428 scopus 로고    scopus 로고
    • An experimental evaluation of ensemble methods for EEG signal classification
    • DOI 10.1016/j.patrec.2007.06.018, PII S0167865507002085
    • Sun S, Zhang C, Zhang D (2007) An experimental evaluation of ensemble methods for EEG signal classification. Pattern Recognit Lett 28:2157-2163 (Pubitemid 47418328)
    • (2007) Pattern Recognition Letters , vol.28 , Issue.15 , pp. 2157-2163
    • Sun, S.1    Zhang, C.2    Zhang, D.3
  • 19
    • 36648998944 scopus 로고    scopus 로고
    • Label propagation through linear neighborhoods
    • Wang F, Zhang C (2008) Label propagation through linear neighborhoods. IEEE Trans Knowl Data Eng 20:55-67
    • (2008) IEEE Trans Knowl Data Eng , vol.20 , pp. 55-67
    • Wang, F.1    Zhang, C.2
  • 20
    • 77955307069 scopus 로고    scopus 로고
    • A modified semi-supervised learning algorithm on Laplacian eigenmaps
    • Zhao Z, Li J, Gao J, Wu X (2010) A modified semi-supervised learning algorithm on Laplacian eigenmaps. Neural Process Lett 32:75-82
    • (2010) Neural Process Lett , vol.32 , pp. 75-82
    • Zhao, Z.1    Li, J.2    Gao, J.3    Wu, X.4
  • 22
    • 28244448186 scopus 로고    scopus 로고
    • Tri-training: Exploiting unlabeled data using three classifiers
    • DOI 10.1109/TKDE.2005.186
    • Zhou Z, Li M (2005) Tri-training: exploiting unlabeled data using three classifiers. IEEE Trans Knowl Data Eng 17:1529-1541 (Pubitemid 41704840)
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.11 , pp. 1529-1541
    • Zhou, Z.-H.1    Li, M.2
  • 23
    • 36348938695 scopus 로고    scopus 로고
    • Semi-supervised learning with very few labeled training examples
    • AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
    • Zhou Z, Zhan D, Yang Q (2007) Semi-supervised learning with very few labeled training examples. In: Proceedings of the twenty-second AAAI conference on artificial intelligence, pp 675-680 (Pubitemid 350149648)
    • (2007) Proceedings of the National Conference on Artificial Intelligence , vol.1 , pp. 675-680
    • Zhou, Z.-H.1    Zhan, D.-C.2    Yang, Q.3
  • 24
    • 33745456231 scopus 로고    scopus 로고
    • Semi-supervised learning literature survey
    • University ofWisconsin, Madison
    • Zhu X(2008) Semi-supervised learning literature survey.Technical Report 1530, University ofWisconsin, Madison
    • (2008) Technical Report , vol.1530
    • Zhu, X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.