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Filtering by: Alternative title ssim Report no. 1665-5 Remove constraint Alternative title ssim: Report no. 1665-5 Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan Resource Type Dissertation Remove constraint Resource Type: Dissertation

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  • Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

    Creator:
    Green, Kevin
    Abstract:
    Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...
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    Dissertation
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    . . . . . . . . . . . . . . . . . . . . . 4 1.2.3 Whole Body Control . . . . . . . . . . . . . . . . . . . . . . 5 1.2.4 Hybrid Zero

  • Characterizing and Addressing Dataset Shift with Deep Learning

    Creator:
    Olson, Matthew L.
    Abstract:
    This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
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    Dissertation
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    , no matter how complicated. My mother for her excellent writing advice. My daughters for constantly

  • The density signature

    Creator:
    Migler-VonDollen, Theresa
    Abstract:
    In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
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    Dissertation
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    the case in existing random graph models. No existing random graph model generates graphs that

  • Action Segmentation with Limited Supervision

    Creator:
    Li, Jun
    Abstract:
    In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
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    of actions present; and (3) Unsupervised learning, where no ground truth is available. To address

  • Uncertainty in Deep Learning with Implicit Neural Networks

    Creator:
    Ratzlaff, Neale
    Abstract:
    The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
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    variational inference that allows for efficient sampling, places no restrictions on the approximate posterior

  • Data-Driven Approaches For Decoding Volitional Movement Intent From Bioelectrical Signals

    Creator:
    Cunha Dantas, Henrique
    Abstract:
    There are nearly two million limb amputees living in the United States of America. Loss of limbs results in profound changes in one's life. However, the underlying neural circuitry and much of the ability to sense and control movements of their missing limb is retained even after limb loss. This...
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    Dissertation
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    were validated using data from two amputee subjects with tran- sradial amputation. After 5 months of

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
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    languages de- spite no language-specific architectural or hyper-parameter tuning, including achieving the

  • Improving automated email tagging with implicit feedback

    Creator:
    Sorower, Mohammad Shahed
    Abstract:
    Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
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    message, no corrections have been made, then perhaps it is safe for the learning system to treat the

  • Deep Learning for Human and Biological Languages

    Creator:
    Hong, Junki
    Abstract:
    We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
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    Dissertation
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    . Focus- ing on the cases where little to no homologous sequences can be found for a given input protein

  • Machine learning for improving the quality of citizen science data

    Creator:
    Yu, Jun
    Abstract:
    Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
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    Dissertation
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    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 TABLE OF CONTENTS (Continued) Page 5 Clustering Species Accumulation Curves to Identify Groups