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Filtering by: Creator van Leeween, P. J. Remove constraint Creator: van Leeween, P. J. Contributor Raich, Raviv Remove constraint Contributor: Raich, Raviv

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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:
    . Raich, X. Z. Fern, and J. P. Arriaga, Multi-instance multi-label learning in the presence of novel class

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation
    Full Text:
    discrete correlation tensor is defined as C(A,B,k) = Ei∈{1,...,N},j∈Zp [I(Xi[k](j) = A)I(Xi(j) = B)]− P (A

  • On Convex Dimensionality Reduction for Classification

    Creator:
    Tammineni, Tez Deepthi
    Abstract:
    Dimensionality reduction (DR) is an efficient approach to reduce the size of data by capturing the informative intrinsic features and discarding the noise. DR methods can be grouped through a variety of categories, e.g. supervised/ unsupervised, linear/non-linear or parametric/non-parametric. Objective function based methods can be grouped into convex and non...
    Resource Type:
    Capstone Project
    Full Text:
    . J̃p(W ) = 1 P P∑ i=1 N∑ j=1 I(ci 6= cj))e−∆X̃ T ijW∆X̃ij where P ≪ N (7.1) The time

  • Multiple Instance Learning for Histopathological Image Classification

    Creator:
    Lai, Phung
    Abstract:
    In histopathological image analysis, image classification as well as pattern detection play a crucial role in the diagnosis and treatment process since the goal is to not only differentiate cancer types but also identify cancerous manifestations. Fully supervised learning strategies tend to address these problems using manually annotated cancerous regions...
    Resource Type:
    Capstone Project