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Filtering by: Creator Anh Tuan Nguyen Remove constraint Creator: Anh Tuan Nguyen Advisor Raich, Raviv Remove constraint Advisor: 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:
    , chi Van Anh, anh Trung, Trang, Dieu Anh, Trang Tran, Tuan, chi Truc, chi Linh, Thai, anh Duong, Huong

  • 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:
    AN ABSTRACT OF THE DISSERTATION OF Tam Nguyen for the

  • A statistical inference framework for finding recurring patterns in large data with applications to energy management

    Creator:
    You, Zeyu
    Abstract:
    We consider the problem of finding unknown patterns that are recurring across multiple sets. For example, finding multiple objects that are present in multiple images or a short DNA code that is repeated across multiple DNA sequences. We first consider a simple problem of finding a single unknown pattern in...
    Resource Type:
    Masters Thesis
    Full Text:
    Nguyen, Prof. Xiaoli Fern and Prof. for their support and advice. I would also like to thank our group

  • Convergence Analysis Framework for Fixed-Point Algorithms in Machine Learning and Signal Processing

    Creator:
    Vu, Trung
    Abstract:
    Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...
    Resource Type:
    Dissertation
    Full Text:
    include Anh Pham, Evgenia Chunikhina, Zeyu You, Tam Nguyen, Phung Lai, Alan Campbell, Hector Dominguez

  • Weak-supervision Time-series Analysis

    Creator:
    You, Zeyu
    Abstract:
    Efficient time-series analysis can impact multiple application domains such as motif discovery in gene analysis or music data, extracting spectro-temporal patterns in acoustic scene analysis, or annotating and classifying electrical bio-signals (such as ECG, EEG, and EMG) for medical applications. Time-series analysis involves a variety of tasks. To predict future...
    Resource Type:
    Dissertation
    Full Text:
    - lished papers. At last but not least, I want to thank our group members, Anh Pham, Tam Nguyen Thi, Thi