Now showing items 1-4 of 4

    • Contributions to Unsupervised and Semi-Supervised Learning 

      Pal, David (University of Waterloo, 2009-05-22)
      This thesis studies two problems in theoretical machine learning. The first part of the thesis investigates the statistical stability of clustering algorithms. In the second part, we study the relative advantage of ...
    • Fundamental Limitations of Semi-Supervised Learning 

      Lu, Tyler (Tian) (University of Waterloo, 2009-05-05)
      The emergence of a new paradigm in machine learning known as semi-supervised learning (SSL) has seen benefits to many applications where labeled data is expensive to obtain. However, unlike supervised learning (SL), which ...
    • Learning from Partially Labeled Data: Unsupervised and Semi-supervised Learning on Graphs and Learning with Distribution Shifting 

      Huang, Jiayuan (University of Waterloo, 2007-08-20)
      This thesis focuses on two fundamental machine learning problems:unsupervised learning, where no label information is available, and semi-supervised learning, where a small amount of labels are given in addition to unlabeled ...
    • Optimization for Image Segmentation 

      Tang, Meng (University of Waterloo, 2019-06-26)
      Image segmentation, i.e., assigning each pixel a discrete label, is an essential task in computer vision with lots of applications. Major techniques for segmentation include for example Markov Random Field (MRF), Kernel ...

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