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Volumn WS-12-08, Issue , 2012, Pages 47-53

Crowdclustering with sparse pairwise labels: A matrix completion approach

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COSTS; HUMAN ANNOTATIONS; MANUAL ANNOTATION; MATRIX COMPLETION; PARTIAL CLUSTERING; SIMILARITY MATRIX; SIMILARITY MEASURE; SPECTRAL CLUSTERING ALGORITHMS;

EID: 84875697110     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (27)

References (22)
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    • 77951528523 scopus 로고    scopus 로고
    • The power of convex relaxation: Near-optimal matrix completion
    • Candès, E. J., and Tao, T. 2010. The power of convex relaxation: near-optimal matrix completion. IEEE Transactions on Information Theory 56(5):2053-2080.
    • (2010) IEEE Transactions on Information Theory , vol.56 , Issue.5 , pp. 2053-2080
    • Candès, E.J.1    Tao, T.2
  • 7
  • 8
    • 80053437868 scopus 로고    scopus 로고
    • Clustering partially observed graphs via convex optimization
    • Jalali, A.; Chen, Y.; Sanghavi, S.; and Xu, H. 2011. Clustering partially observed graphs via convex optimization. In ICML, 1001-1008.
    • (2011) ICML , pp. 1001-1008
    • Jalali, A.1    Chen, Y.2    Sanghavi, S.3    Xu, H.4
  • 9
    • 85162483531 scopus 로고    scopus 로고
    • Iterative learning for reliable crowdsourcing systems
    • Karger, D.; Oh, S.; and Shah, D. 2011. Iterative learning for reliable crowdsourcing systems. In NIPS.
    • (2011) NIPS
    • Karger, D.1    Oh, S.2    Shah, D.3
  • 10
    • 49749129595 scopus 로고    scopus 로고
    • Solving consensus and semi-supervised clustering problems using non-negative matrix factorization
    • Li, T.; Ding, C. H. Q.; and Jordan, M. I. 2007. Solving consensus and semi-supervised clustering problems using non-negative matrix factorization. In Seventh IEEE International Conference on Data Mining, 577-582.
    • (2007) Seventh IEEE International Conference on Data Mining , pp. 577-582
    • Li, T.1    Ding, C.H.Q.2    Jordan, M.I.3
  • 13
    • 0041875229 scopus 로고    scopus 로고
    • On spectral clustering: Analysis and an algorithm
    • Ng, A. Y.; Jordan, M. I.; and Weiss, Y. 2001. On spectral clustering: Analysis and an algorithm. In NIPS, 849-856.
    • (2001) NIPS , pp. 849-856
    • Ng, A.Y.1    Jordan, M.I.2    Weiss, Y.3
  • 14
    • 85162536261 scopus 로고    scopus 로고
    • Ranking annotators for crowdsourced labeling tasks
    • Raykar, V., and Yu, S. 2011. Ranking annotators for crowdsourced labeling tasks. In NIPS.
    • (2011) NIPS
    • Raykar, V.1    Yu, S.2
  • 17
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles - A knowledge reuse framework for combining multiple partitions
    • Strehl, A., and Ghosh, J. 2002. Cluster ensembles - a knowledge reuse framework for combining multiple partitions. JMLR 3:583-617.
    • (2002) JMLR , vol.3 , pp. 583-617
    • Strehl, A.1    Ghosh, J.2
  • 18
    • 80053456767 scopus 로고    scopus 로고
    • Adaptively learning the crowd kernel
    • Getoor, L., and Scheffer, T., eds., Omnipress
    • Tamuz, O.; Liu, C.; Belongie, S.; Shamir, O.; and Kalai, A. 2011. Adaptively learning the crowd kernel. In Getoor, L., and Scheffer, T., eds., ICML, 673-680. Omnipress.
    • (2011) ICML , pp. 673-680
    • Tamuz, O.1    Liu, C.2    Belongie, S.3    Shamir, O.4    Kalai, A.5
  • 19
    • 80052905596 scopus 로고    scopus 로고
    • Large-scale live active learning: Training object detectors with crawled data and crowds
    • Vijayanarasimhan, S., and Grauman, K. 2011. Large-scale live active learning: Training object detectors with crawled data and crowds. In CVPR, 1449-1456.
    • (2011) CVPR , pp. 1449-1456
    • Vijayanarasimhan, S.1    Grauman, K.2
  • 20
    • 85162481803 scopus 로고    scopus 로고
    • Bayesian bias mitigation for crowdsourcing
    • Wauthier, F., and Jordan, M. 2011. Bayesian bias mitigation for crowdsourcing. In NIPS.
    • (2011) NIPS
    • Wauthier, F.1    Jordan, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.