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Filtering by: Alternative title ssim FG 7 Remove constraint Alternative title ssim: FG 7 Contributor Raich, Raviv Remove constraint Contributor: Raich, Raviv Resource Type Dissertation Remove constraint Resource Type: Dissertation

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  • Weak-supervision : Probabilistic Models and Inference

    Creator:
    Pham, Anh
    Abstract:
    In supervised learning, label information can be provided at different levels of granularity. For small datasets, it is possible to acquire a label for each data instance. However, in the big-data regime, this fine granularity approach is prohibitively costly. For example, in semi-supervised learning, only a limited number of samples...
    Resource Type:
    Dissertation
    Full Text:
    approaches for weak-supervision learning . . . . . . . . . . . . . . . 7 1.3.1 Recent approaches for MIL

  • Multiple Instance Multiple Label Learning with Limited Supervision

    Creator:
    Nguyen, Tam
    Abstract:
    In weak supervision learning, label information can be provided at different levels of granularity. For example, in multi-instance multi-label learning, samples are organized into bags and labels for each class are provided at the bag level. For small datasets, this approach offers means of reducing the labeling efforts. However, in...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . 7 1.3.3 Active learning in MIML . . . . . . . . . . . . . . . . . . . . . . . 8 1.4 Challenges