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  • Efficient Algorithms for Robust Spatiotemporal Data Analysis

    Creator:
    Moore, Travis W.
    Abstract:
    Many large-scale data analysis applications involve data that can vary over both time and space. Often the primary goal of analyzing spatiotemporal data is identifying trends, movements, and sudden changes with respect to time, location, or both. This can include a variety of applications in economics (housing prices, unemployment, job...
    Resource Type:
    Dissertation

  • Dimensionality Reduction Techniques for Compositional Data : An Empirical Study

    Creator:
    George, Rogen
    Abstract:
    Compositional data is a type of data where the features are non-negative and always sum to a constant. This type of data is frequently encountered in many fields such as microbiology, geology, economics and natural language processing. Compositional data has unique statistical properties that makes it difficult to apply standard...
    Resource Type:
    Masters Thesis
    Full Text:
    . Xiaoli Fern who is a part of my committee. I thank Doug Robinson, Tyler Hallman and Jenna Curtis for the

  • Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression

    Creator:
    Wang, Xinyao
    Abstract:
    Heatmap regression has became one of the mainstream approaches to localize facial landmarks. As Convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) are becoming popular in solving computer vision tasks, extensive research has been done on these architectures. However, the loss function for heatmap regression is rarely studied. In...
    Resource Type:
    Masters Thesis
    Full Text:
    committee members. Professor Xiaoli Fern introduced the world of machine learning to me. My research on

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation
    Full Text:
    other thesis committee members, Professor Fuxin Li, Professor Raviv Raich and Professor Xiaoli Fern. I

  • Learning Topical Social Media Sensors for Twitter

    Creator:
    Iman, Zahra
    Abstract:
    Social media sources such as Twitter represent a massively distributed social sensor over diverse topics ranging from social and political events to entertainment and sports news. However, due to the overwhelming volume of content, it can be difficult to identify novel and significant content within a broad topic in a...
    Resource Type:
    Masters Thesis

  • 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:
    time were Dr. Xiao Fu, Dr. Jinsub Kim, and Dr. Xiaoli Fern, who have contributed their expertise and

  • Infant Hand Detection and Tracking

    Creator:
    Mishra, Shridhar
    Abstract:
    Hand detection is a fundamental step for many hand-related computer vision tasks, such as gesture recognition, hand pose estimation, hand sign language translation, and so on. However, robustly detecting hands is a challenging task because of drastic changes in appearance based on finger articulation and changes in lighting conditions, camera...
    Resource Type:
    Masters Thesis
    Full Text:
    also thank Prof Alan Fern, Sinisa Todorovic, and Xiaoli Fern for mentoring me throughout the work done

  • Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

    Creator:
    Seo, Eugene
    Abstract:
    Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...
    Resource Type:
    Dissertation
    Full Text:
    , I would like to show gratitude to my committee, including Dr. Thomas G. Dietterich, Dr. Xiaoli Fern

  • 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:
    support I would not be where I am today. I would like to thank Dr. Xiao-li Fern for providing useful

  • Two Sides of a Coin: Adversarial-Based Image Privacy and Defending Against Adversarial Perturbations for Robust CNNs

    Creator:
    Rajabi, Arezoo
    Abstract:
    Emergence of highly accurate Convolutional Neural Networks (CNNs) with the capability to process large datasets, has led to their popularity in many applications, including safety/security-sensitive (e.g. disease recognition, self-driving cars). Despite the high accuracy of convolutional neural networks, they have been found to be susceptible to adversarial noise added to...
    Resource Type:
    Dissertation
    Full Text:
    . Xiaoli Fern and Dr. Mike Rosulek for all of their invaluable feedback, support, and for selflessly