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Filtering by: Creator McFadden, Andrew K. Remove constraint Creator: McFadden, Andrew K. 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

  • 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

  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    select k ≥ 1 points to be evaluated. The results of those points are then added to the set of

  • Resource placement, data rearrangement, and Hamiltonian cycles in torus networks

    Creator:
    Bae, Myung Mun
    Abstract:
    Many parallel machines, both commercial and experimental, have been/are being designed with toroidal interconnection networks. For a given number of nodes, the torus has a relatively larger diameter, but better cost/performance tradeoffs, such as higher channel bandwidth, and lower node degree, when compared to the hypercube. Thus, the torus is...
    Resource Type:
    Dissertation
    Full Text:
    . The last part of the thesis gives results on generating edge disjoint Hamilto­ nian cycles in k-ary n

  • 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:
    -k Policy . . . . . . . . . . . . . . . . . . . . . 7 2.1.1 Latency Metric: Average Lagging

  • Knowledge Base Completion Leveraging Natural Language Data

    Creator:
    Shahbazi, Hamed
    Abstract:
    Information about named entities (real-world objects) is usually harvested from different sources and organized as a multiple relational directed graph in Knowledge Bases (KBs). KBs play essential roles in many NLP modules including question answering, fact-checking, search engines, etc. KBs are big but still incomplete: relational information among entities is...
    Resource Type:
    Dissertation
    Full Text:
    [27] introduce a soft k-max attention model to weigh the importance of other entities in the document

  • Scheduling and Online Planning in Stochastic Diffusion Networks

    Creator:
    Xue, Shan
    Abstract:
    Diffusion processes in networks are common models for many domains, including species colonization, information/idea cascade, disease propagation and fire spreading. In diffusion networks, a diffusion event occurs when a behavior spreads from one node to the other following a probabilistic model, where the behavior could be species, an idea, a...
    Resource Type:
    Dissertation
    Full Text:
    marketing setting, Kempe et al. [34] address the problem of selecting k of individuals to initiate a

  • Topics in toroidal interconnection networks

    Creator:
    Broeg, Robert Richard
    Resource Type:
    Dissertation
    Full Text:
    characterized as a graph that is the cross product of cycles. The graphs of the k-ary n-cube (Qk,,) and the

  • 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:
    an integer lattice structure, i.e., Xi = {Xi(k),k ∈ Zp} where k is a p-dimensional index vector. Let