메뉴 건너뛰기




Volumn , Issue , 2009, Pages 585-593

Graph-based consensus maximization among multiple supervised and unsupervised models

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; GRAPH THEORY; GRAPHIC METHODS; ITERATIVE METHODS;

EID: 84863338443     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (100)

References (29)
  • 1
  • 2
    • 0032645080 scopus 로고    scopus 로고
    • An empirical comparison of voting classification algorithms: Bagging, boosting, and variants
    • E. Bauer and R. Kohavi. An Empirical Comparison of Voting Classification Algorithms: Bagging, Boosting, and Variants. Machine Learning, 36:105-139, 2004.
    • (2004) Machine Learning , vol.36 , pp. 105-139
    • Bauer, E.1    Kohavi, R.2
  • 4
    • 0031620208 scopus 로고    scopus 로고
    • Combining labeled and unlabeled data with co-training
    • A. Blum and T. Mitchell. Combining Labeled and Unlabeled Data with Co-training. In Proc. of COLT' 98, pages 92-100, 1998.
    • (1998) Proc. of COLT' 98 , pp. 92-100
    • Blum, A.1    Mitchell, T.2
  • 6
    • 0031189914 scopus 로고    scopus 로고
    • Multitask learning
    • R. Caruana. Multitask Learning. Machine Learning, 28:41-75, 1997.
    • (1997) Machine Learning , vol.28 , pp. 41-75
    • Caruana, R.1
  • 10
    • 33745582166 scopus 로고    scopus 로고
    • DBLP Bibliography. http://www.informatik.uni-trier.de/~ley/db/.
    • DBLP Bibliography
  • 11
    • 80053403826 scopus 로고    scopus 로고
    • Ensemble methods in machine learning
    • T. Dietterich. Ensemble Methods in Machine Learning. In Proc. of MCS '00, pages 1-15, 2000.
    • (2000) Proc. of MCS '00 , pp. 1-15
    • Dietterich, T.1
  • 12
    • 14344258244 scopus 로고    scopus 로고
    • Solving cluster ensemble problems by bipartite graph partitioning
    • X. Z. Fern and C. E. Brodley. Solving Cluster Ensemble Problems by Bipartite Graph Partitioning. In Proc. of ICML' 04, pages 281-288, 2004.
    • (2004) Proc. of ICML' 04 , pp. 281-288
    • Fern, X.Z.1    Brodley, C.E.2
  • 13
    • 72449138529 scopus 로고    scopus 로고
    • Multi-view learning over structured and non-identical outputs
    • K. Ganchev, J. Graca, J. Blitzer, and B. Taskar. Multi-view Learning over Structured and Non-identical Outputs. In Proc. of UAI' 08, pages 204-211, 2008.
    • (2008) Proc. of UAI' 08 , pp. 204-211
    • Ganchev, K.1    Graca, J.2    Blitzer, J.3    Taskar, B.4
  • 14
    • 70350681831 scopus 로고    scopus 로고
    • Heterogeneous source consensus learning via decision propagation and negotiation
    • J. Gao, W. Fan, Y. Sun, and J. Han. Heterogeneous source consensus learning via decision propagation and negotiation. In Proc. of KDD' 09, pages 339-347, 2009.
    • (2009) Proc. of KDD' 09 , pp. 339-347
    • Gao, J.1    Fan, W.2    Sun, Y.3    Han, J.4
  • 16
    • 47749130308 scopus 로고    scopus 로고
    • Seeing stars when there aren't many stars: Graph-based semi-supervised learning for sentiment categorization
    • A. Goldberg and X. Zhu. Seeing stars when there aren't many stars: Graph-based semi-supervised learning for sentiment categorization. In HLT-NAACL 2006 Workshop on Textgraphs.
    • HLT-NAACL 2006 Workshop on Textgraphs
    • Goldberg, A.1    Zhu, X.2
  • 18
    • 0041848443 scopus 로고    scopus 로고
    • Topic-sensitive PageRank: A context-sensitive ranking algorithm for web search
    • T. Haveliwala. Topic-Sensitive PageRank: A Context-Sensitive Ranking Algorithm for Web Search. IEEE Transactions on Knowledge and Data Engineering, 15(4):1041-4347, 2003.
    • (2003) IEEE Transactions on Knowledge and Data Engineering , vol.15 , Issue.4 , pp. 1041-4347
    • Haveliwala, T.1
  • 21
    • 1942484960 scopus 로고    scopus 로고
    • Transductive learning via spectral graph partitioning
    • T. Joachims. Transductive Learning via Spectral Graph Partitioning. In Proc. of ICML' 03, pages 290-297, 2003.
    • (2003) Proc. of ICML' 03 , pp. 290-297
    • Joachims, T.1
  • 26
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles - A knowledge reuse framework for combining multiple partitions
    • A. Strehl and J. Ghosh. Cluster Ensembles - a Knowledge Reuse Framework for Combining Multiple Partitions. Journal of Machine Learning Research, 3:583-617, 2003.
    • (2003) Journal of Machine Learning Research , vol.3 , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 27
    • 0026692226 scopus 로고
    • Stacked generalization
    • D. Wolpert. Stacked Generalization. Neural Networks, 5:241-259, 1992.
    • (1992) Neural Networks , vol.5 , pp. 241-259
    • Wolpert, D.1
  • 29
    • 33745456231 scopus 로고    scopus 로고
    • Semi-supervised learning literature survey
    • University of Wisconsin-Madison
    • X. Zhu. Semi-supervised Learning Literature Survey. Technical Report 1530, Computer Sciences, University of Wisconsin-Madison, 2005.
    • (2005) Technical Report 1530, Computer Sciences
    • Zhu, X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.