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Volumn 35, Issue 2, 2013, Pages 345-364

Structured feature selection and task relationship inference for multi-task learning

Author keywords

Multi task learning; Structural sparsity; Structured input and structured output; Task relationship inference

Indexed keywords

CLUSTERING ALGORITHMS; COVARIANCE MATRIX; FEATURE EXTRACTION; GRADIENT METHODS; LEARNING SYSTEMS; LINEARIZATION; MULTI-TASK LEARNING; OPTIMIZATION;

EID: 84876033996     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-012-0543-4     Document Type: Article
Times cited : (31)

References (52)
  • 1
    • 57749097129 scopus 로고    scopus 로고
    • A spectral regularization framework for multi-task structure learning
    • Argyriou A, Micchelli A, Pontil M, Ying Y (2007) A spectral regularization framework for multi-task structure learning. In: NIPS.
    • (2007) NIPS
    • Argyriou, A.1    Micchelli, A.2    Pontil, M.3    Ying, Y.4
  • 3
    • 0346238931 scopus 로고    scopus 로고
    • Task clustering and gating for bayesian multitask learning
    • Bakker B, Heskes T (2003) Task clustering and gating for bayesian multitask learning. J Mach Learn Res 4: 83-99.
    • (2003) J Mach Learn Res , vol.4 , pp. 83-99
    • Bakker, B.1    Heskes, T.2
  • 6
    • 84867734798 scopus 로고    scopus 로고
    • A Countably Infinite Mixture Model For Clustering and Feature Selection
    • ISSN 0219-1377. doi: 10. 1007/s10115-011-0467-4
    • Bouguila N, Ziou D (2011) A countably infinite mixture model for clustering and feature selection. Knowl Inf Syst, pp 1-20, ISSN 0219-1377. doi: 10. 1007/s10115-011-0467-4.
    • (2011) Knowl Inf Syst , pp. 1-20
    • Bouguila, N.1    Ziou, D.2
  • 11
    • 80052677096 scopus 로고    scopus 로고
    • Integrating Low-rank and Group-sparse Structures For Robust Multi-task Learning
    • Chen J, Zhou J, Ye J (2011) Integrating low-rank and group-sparse structures for robust multi-task learning. In: KDD, pp 42-50.
    • (2011) KDD , pp. 42-50
    • Chen, J.1    Zhou, J.2    Ye, J.3
  • 12
    • 79951737128 scopus 로고    scopus 로고
    • Scalable Influence Maximization In Social Networks Under the Linear Threshold Model
    • Chen W, Yuan Y, Zhang L (2010) Scalable influence maximization in social networks under the linear threshold model. In: ICDM, pp 88-97.
    • (2010) ICDM , pp. 88-97
    • Chen, W.1    Yuan, Y.2    Zhang, L.3
  • 14
    • 12244250351 scopus 로고    scopus 로고
    • Regularized Multi-task Learning
    • Evgeniou T, Pontil M (2004) Regularized multi-task learning. In: KDD, pp 109-117.
    • (2004) KDD , pp. 109-117
    • Evgeniou, T.1    Pontil, M.2
  • 19
    • 84859106212 scopus 로고    scopus 로고
    • Highly discriminative statistical features for email classification
    • Gomez J-C, Boiy E, Moens M-F (2012) Highly discriminative statistical features for email classification. Knowl Inf Syst 31(1): 23-53.
    • (2012) Knowl Inf Syst , vol.31 , Issue.1 , pp. 23-53
    • Gomez, J.-C.1    Boiy, E.2    Moens, M.-F.3
  • 22
    • 71149103464 scopus 로고    scopus 로고
    • An accelerated gradient method for trace norm minimization
    • ACM, New York, NY, USA, ISBN 978-1-60558-516-1
    • Ji S, Ye J (2009) An accelerated gradient method for trace norm minimization. In: ICML '09: Proceedings of the 26th annual international conference on machine learning. ACM, New York, NY, USA, pp 457-464, ISBN 978-1-60558-516-1. http://doi. acm. org/10. 1145/1553374. 1553434.
    • (2009) ICML '09: Proceedings of the 26th Annual International Conference On Machine Learning , pp. 457-464
    • Ji, S.1    Ye, J.2
  • 25
    • 84859904592 scopus 로고    scopus 로고
    • gMLC: a multi-label feature selection framework for graph classification
    • Kong X, Yu PS (2012) gMLC: a multi-label feature selection framework for graph classification. Knowl Inf Syst 31(2): 281-305.
    • (2012) Knowl Inf Syst , vol.31 , Issue.2 , pp. 281-305
    • Kong, X.1    Yu, P.S.2
  • 27
    • 42649140560 scopus 로고    scopus 로고
    • Network-constrained regularization and variable selection for analysis of genomic data
    • Li C, Li H (2008) Network-constrained regularization and variable selection for analysis of genomic data. Bioinformatics 24(9): 1175-1182.
    • (2008) Bioinformatics , vol.24 , Issue.9 , pp. 1175-1182
    • Li, C.1    Li, H.2
  • 30
    • 84871530889 scopus 로고    scopus 로고
    • Taking advantage of sparsity in multi-task learning
    • Lounici K, Pontil M, van De Geer S (2009) Taking advantage of sparsity in multi-task learning. Knowl Inf Syst 20(1): 109-348.
    • (2009) Knowl Inf Syst , vol.20 , Issue.1 , pp. 109-348
    • Lounici, K.1    Pontil, M.2    van de Geer, S.3
  • 31
    • 45749091592 scopus 로고    scopus 로고
    • Predicting human brain activity associated with the meanings of nouns
    • Mitchell TM, Shinkareva SV, Andrew A et al (2008) Predicting human brain activity associated with the meanings of nouns. Science 320: 1191-1195.
    • (2008) Science , vol.320 , pp. 1191-1195
    • Mitchell, T.M.1    Shinkareva, S.V.2    Andrew, A.3
  • 33
    • 57649169327 scopus 로고    scopus 로고
    • Gradient methods for minimizing composite objective function
    • Nesterov Y (2007) Gradient methods for minimizing composite objective function. CORE Disc Paper 76: 265-286.
    • (2007) CORE Disc Paper , vol.76 , pp. 265-286
    • Nesterov, Y.1
  • 34
    • 0037381008 scopus 로고    scopus 로고
    • Gene expression-based classification of malignant gliomas correlates better with survival than histological classification
    • Nutt CL, Mani DR, Betensky RA et al (2003) Gene expression-based classification of malignant gliomas correlates better with survival than histological classification. Cancer Res 63: 1602-1607.
    • (2003) Cancer Res , vol.63 , pp. 1602-1607
    • Nutt, C.L.1    Mani, D.R.2    Betensky, R.A.3
  • 35
    • 84876067592 scopus 로고    scopus 로고
    • National Institute of Health
    • National Institute of Health (2010) Metastatic cancer. http://www.cancer.gov/cancertopics/factsheet/Sites-Types/metastatic.
    • (2010) Metastatic cancer
  • 38
  • 40
    • 19044391072 scopus 로고    scopus 로고
    • Gene Expression Correlates of Clinical Prostate Cancer Behavior
    • ISSN 1535-6108
    • Singh D, Febbo PG et al (2002) Gene expression correlates of clinical prostate cancer behavior. Cancer cell 1(2): 203-209, ISSN 1535-6108.
    • (2002) Cancer Cell , vol.1 , Issue.2 , pp. 203-209
    • Singh, D.1    Febbo, P.G.2
  • 41
    • 0035887459 scopus 로고    scopus 로고
    • Molecular classification of human carcinomas by use of gene expression signatures
    • Su AI, Welsh JB, Sapinoso LM et al (2001) Molecular classification of human carcinomas by use of gene expression signatures. Cancer Res 15(20): 7388-7393.
    • (2001) Cancer Res , vol.15 , Issue.20 , pp. 7388-7393
    • Su, A.I.1    Welsh, J.B.2    Sapinoso, L.M.3
  • 43
    • 0036632368 scopus 로고    scopus 로고
    • The phosphatidylinositol 3-kinase akt pathway in human cancer
    • Vivanco I, Sawyers CL (2002) The phosphatidylinositol 3-kinase akt pathway in human cancer. Nat Rev Cancer 2(7): 489-501.
    • (2002) Nat Rev Cancer , vol.2 , Issue.7 , pp. 489-501
    • Vivanco, I.1    Sawyers, C.L.2
  • 44
    • 84863119915 scopus 로고    scopus 로고
    • Multi-task Learning With Task Relations
    • Xu Z, Kersting K (2011) Multi-task learning with task relations. In: ICDM, pp 884-893.
    • (2011) ICDM , pp. 884-893
    • Xu, Z.1    Kersting, K.2
  • 45
    • 79951755129 scopus 로고    scopus 로고
    • Modeling Information Diffusion In Implicit Networks
    • Yang J, Leskovec J (2010) Modeling information diffusion in implicit networks. In: ICDM, pp 599-608.
    • (2010) ICDM , pp. 599-608
    • Yang, J.1    Leskovec, J.2
  • 46
    • 0001765951 scopus 로고    scopus 로고
    • A direct LDA algorithm for high-dimensional data with application to face recognition
    • Yu H, Yang J (2001) A direct LDA algorithm for high-dimensional data with application to face recognition. Pattern Recognit 34(10): 2067-2070.
    • (2001) Pattern Recognit , vol.34 , Issue.10 , pp. 2067-2070
    • Yu, H.1    Yang, J.2
  • 48
    • 84857146284 scopus 로고    scopus 로고
    • Multi-task Learning For Bayesian Matrix Factorization
    • Yuan C (2011) Multi-task learning for bayesian matrix factorization. In: ICDM, pp 924-931.
    • (2011) ICDM , pp. 924-931
    • Yuan, C.1
  • 51
    • 84867734798 scopus 로고    scopus 로고
    • A Countably Infinite Mixture Model For Clustering and Feature Selection
    • ISSN 0219-1377. doi: 10. 1007/s10115-011-0467-4
    • Bouguila N, Ziou D (2011) A countably infinite mixture model for clustering and feature selection. Knowl Inf Syst, pp 1-20, ISSN 0219-1377. doi: 10. 1007/s10115-011-0467-4.
    • (2011) Knowl Inf Syst , pp. 1-20
    • Bouguila, N.1    Ziou, D.2
  • 52
    • 80052666240 scopus 로고    scopus 로고
    • A multi-task learning formulation for predicting disease progression
    • Zhou J, Yuan L, Liu J, Ye J (2011) A multi-task learning formulation for predicting disease progression. In: KDD, pp 814-822.
    • (2011) KDD , pp. 814-822
    • Zhou, J.1    Yuan, L.2    Liu, J.3    Ye, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.