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Filtering by: Creator Ezell, Andrew W. Remove constraint Creator: Ezell, Andrew W. Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • A Benchmarking Study of Unsupervised Anomaly Detection Algorithms

    Creator:
    Emmott, Andrew F.
    Abstract:
    It is common practice in the unsupervised anomaly detection literature to create experimental benchmarks by sampling from existing supervised learning datasets. We seek to improve this practice by identifying four dimensions important to real-world anomaly detection applications --- point difficulty, clusteredness of anomalies, relevance of features, and relative frequency of...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Andrew Emmott for the

  • Learning-based Control of Experimental Hybrid Fuel Cell Power Plant

    Creator:
    Gabler, Andrew
    Abstract:
    Direct red Solid Oxide Fuel Cell (SOFC) Turbine hybrid plants have the potential to dramatically increase power plant efficiency, decrease emissions, and provide fast response to transient loads. The US Department of Energy's (DOE) Hybrid Performance Project is an experimental hybrid SOFC plant, built at the National Energy Technology Laboratory...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Andrew Gabler for the degree of

  • Toward computer vision for understanding American football in video

    Creator:
    Hess, Robin W.
    Abstract:
    In this work, I examine the problem of understanding American football in video. In particular, I present several mid-level computer vision algorithms that each accomplish a different sub-task within a larger system for annotating, interpreting, and analyzing collections of American football video. The analysis of football video is useful in...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Robin W. Hess for the

  • Microstructure of radiation damage in the uranium film and its backing materials irradiated with 136 MeV 136Xe+26, Microstructure of radiation damage in the uranium film and its backing materials irradiated with 136 MeV ¹³⁶Xe⁺²⁶

    Creator:
    Sadi, Supriyadi
    Abstract:
    Microstructure changes in uranium and uranium/metal alloys due to radiation damage are of great interest in nuclear science and engineering. Titanium has attracted attention because of its similarity to Zr. It has been proposed for use in the second generation of fusion reactors due to its resistance to radiation-induced swelling....
    Resource Type:
    Dissertation
    Full Text:
    facilities during this thesis project. I would like to thank Dr. Andrew C. Klein and Dr. David M. Hamby for

  • 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:
    basis (~r, ~w,~v) can be generated from ~rαµ and nµ with the Gram-Schmidt process, and viewpoint

  • Machine learning methods for public policy : simulation, optimization, and visualization

    Creator:
    McGregor, Sean
    Abstract:
    Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
    Resource Type:
    Dissertation
    Full Text:
    for bugs whose underlying cause can be ascribed to several different components. For example, Andrew

  • Structured learning with latent variables : theory and algorithms

    Creator:
    Zhao, Kai
    Abstract:
    Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
    Resource Type:
    Dissertation
    Full Text:
    modeled by some statistical model with parameters w. So F can also be written as Fw. This problem is

  • Incorporating User Feedback into Machine Learning Systems

    Creator:
    Das, Shubhomoy
    Abstract:
    Although machine learning systems are often effective in real-world applications, there are situations in which they can be even better when provided with some degree of end user feedback. This is especially true when the machine learning system needs to customize itself to the end user's preferences, such as in...
    Resource Type:
    Dissertation
    Full Text:
    -likelihood of data in LWLR is computed with respect to the query instance 14 xq as: lw(θ) = N∑ i=1 w(xq

  • Advances in Simultaneous Translation

    Creator:
    Zheng, Renjie
    Abstract:
    Simultaneous translation, which translates concurrently with the source language speech, is widely used in many scenarios including multilateral organizations. However, it is well known to be one of the most challenging tasks for humans due to the simultaneous perception and production in two languages. On the other hand, simultaneous translation...
    Resource Type:
    Dissertation
    Full Text:
    words). . . . . . . 20 2.3 An example for READ/WRITE action sequence. R represents READ and W

  • Learning greedy policies for the easy-first framework

    Creator:
    Xie, Jun
    Abstract:
    Easy-first, a search-based structured prediction approach, has been applied to many NLP tasks including dependency parsing and coreference resolution. This approach employs a learned greedy policy (action scoring function) to make easy decisions first, which constrains the remaining decisions and makes them easier. This thesis studies the problem of learning...
    Resource Type:
    Masters Thesis
    Full Text:
    ) = w · φ(a), where w is the weight vector and φ(·) is a predefined feature function. Note that the