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Volumn , Issue , 2011, Pages 47-50

Designing for effective end-user interaction with machine learning

Author keywords

End user interactive machine learning

Indexed keywords

DESIGN STRATEGIES; DOMAIN SPECIFIC; END USERS; END-USER INTERACTIVE MACHINE LEARNING; HUMAN CAPABILITY; LARGE DATA;

EID: 80955143401     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2046396.2046416     Document Type: Conference Paper
Times cited : (17)

References (14)
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    • CHI 2010 , pp. 1357-1360
    • Amershi, S.1    Fogarty, J.2    Kapoor, A.3    Tan, D.4
  • 2
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    • Overview-based examples selection in mixed-initiative interactive concept learning
    • Amershi, S., Fogarty, J., Kapoor, A. and Tan, D. Overview-Based Examples Selection in Mixed-Initiative Interactive Concept Learning. UIST 2009, 247-256.
    • UIST 2009 , pp. 247-256
    • Amershi, S.1    Fogarty, J.2    Kapoor, A.3    Tan, D.4
  • 4
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    • Query learning can work poorly when a human oracle is used
    • Baum, E.B. and Lang, K. Query Learning can work Poorly when a Human Oracle is Used. Neural Networks 1992.
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    • Baum, E.B.1    Lang, K.2
  • 5
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    • A CAPpella: Programming by demonstrations of context-aware applications
    • Dey, A.K., Hamid, R., Beckmann, C., Li, I. and Hsu, D. a CAPpella: Programming by Demonstrations of Context-Aware Applications. CHI 2004, 33-40.
    • CHI 2004 , pp. 33-40
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  • 7
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    • CueFlik: Interactive concept learning in image search
    • Fogarty, J., Tan. D., Kapoor, A. and Winder, S. CueFlik: Interactive Concept Learning in Image Search. CHI 2008, 29-38.
    • CHI 2008 , pp. 29-38
    • Fogarty, J.1    Tan, D.2    Kapoor, A.3    Winder, S.4
  • 8
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    • Gardner, R.D. and Harle, D.A. Methods and Systems for Alarm Correlation. GLOBECOM 1996, 136-140.
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    • Gardner, R.D.1    Harle, D.A.2
  • 10
    • 84858775391 scopus 로고    scopus 로고
    • Online metric learning and fast similarity search
    • Jain, P., Kulis, B., Dhillon, I.S., and Grauman, K. Online Metric Learning and Fast Similarity Search. NIPS 2008, 761-768.
    • NIPS 2008 , pp. 761-768
    • Jain, P.1    Kulis, B.2    Dhillon, I.S.3    Grauman, K.4
  • 11
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    • Near-optimal sensor placements in Gaussian processes: Theory, efficient algorithms and empirical studies
    • Krause, A., Singh, A. and Guestrin, C. Near-optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies. Journal of Machine Learning Research 9 (2008), 235-284. (Pubitemid 351469021)
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  • 12
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    • Learning to generalize for complex selection tasks
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  • 13
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    • A survey of fault localization techniques in computer networks
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  • 14
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    • Support vector machine active learning for image retrieval
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.