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Filtering by: Creator Nguyen, Bao Committee Member Kim, Jinsub

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
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:

- li Fern, Dr. Jinsub Kim, Dr. Thinh Nguyen, and Dr. Matt Campbell, for their unconditional support
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