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Filtering by: Creator Barlow, Zachary W. Remove constraint Creator: Barlow, Zachary W. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • A case for application-based linear transformers : applied towards text-to-spectrogram

    Creator:
    Agostinelli, Victor
    Abstract:
    Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
    Resource Type:
    Masters Thesis
    Full Text:
    new sub-space via weight matrices W qh in Rdk×dkh , W kh in Rdk×dkh , and W vh in Rdv×dvh for some

  • A Distributed Scheme for Accelerating and Scaling PSPNet

    Creator:
    Krishna, Ajay
    Abstract:
    Advances in deep learning based image processing have led to their adoption for a wide range of applications, and in tow with these developments is a dramatic increase in the availability of high quality datasets. With this comes the need to accelerate and scale deep learning applications in order to...
    Resource Type:
    Masters Thesis
    Full Text:
    , W. Dong, R. Socher, L. Li, Kai Li, and Li Fei-Fei. Imagenet: A large- scale hierarchical image

  • Accuracy enhancement techniques in low-voltage high-speed pipelined ADC design

    Creator:
    Li, Jipeng
    Abstract:
    Pipelined analog to digital converters (ADCs) are very important building blocks in many electronic systems such as high quality video systems, high performance digital communication systems and high speed data acquisition systems. The rapid development of these applications is driving the design of pipeline ADCs towards higher speed, higher dynamic...
    Resource Type:
    Dissertation

  • An Anthology of Next-Generation WSNs and Transformative IoT Use-Cases

    Creator:
    Williams, Jennifer M.
    Abstract:
    The Internet of Things (IoT) paradigm brought an ever-increasing dependence on low-power devices to collect sensor data and transmit that information to the cloud, placing greater demand on connectivity and lifespan. In response, rapid worldwide innovation demonstrates the trade-offs in processing, communication, and energy consumption with diverse approaches to low-power...
    Resource Type:
    Dissertation
    Full Text:
    Pisharody, Jiejie Wang, Gao (Frank) Liu, Laura Rumbel, Lelia Barlow, and Eric Bjorge. With all of my heart I

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    PRES RELH RAIN WDSD SRAD TAIR TA9M WDIR WSSD WMAX WS2M WSPD WVEC PR ES RE LH RA IN W DS

  • Atomic Layer Deposition of Multi-Insulator Metal-Insulator-Metal Capacitors

    Creator:
    Austin, Dustin Z.
    Abstract:
    Back end of line (BEOL) metal-insulator-metal capacitors (MIMCAPs) have become a core passive component in modern integrated circuits. International Technology Roadmap for Semiconductors (ITRS) projections for scaling of analog/mixed-signal MIMCAP applications require simultaneously increasing capacitance density while maintaining low leakage current density and low voltage nonlinearity (characterized by the quadratic...
    Resource Type:
    Dissertation
    Full Text:
    DISSERTATION OF Dustin Zachary Austin for the degree of Doctor of Philosophy in Electrical and Computer

  • Atomic Layer Processing for Next-Generation Microelectronic Materials

    Creator:
    Holden, Konner E. K.
    Abstract:
    Atomic layer deposition (ALD) is an enabling technique for many new micro- and nanoscale technologies. The self-limiting surface chemical reactions by which ALD fundamentally operates give rise to uniquely high precision (atomic) control over deposited film thickness, uniformity over large areas, and conformality over complex and extreme topographies. One such...
    Resource Type:
    Dissertation
    Full Text:
    support a 1000 W Xe(Hg) arc lamp directly above the wafer.. ........................... 97 Figure

  • Atomic solid state energy scale applied to novel thin-film solar absorbers

    Creator:
    Pelatt, Brian D.
    Abstract:
    The atomic solid state energy (SSE) scale is introduced as a tool for inorganic materials design. The SSE scale is obtained by assessing an average electron affinity (EA) (for a cation) or an average ionization potential (IP) (for an anion) for each atom using data from compounds having that specific...
    Resource Type:
    Dissertation
    Full Text:
    sun’s spectrum outside the earth’s atmosphere and is approximately 1325 W/m2. The AM1 spectrum

  • Building Self Adaptive Software Systems via Test-based Modifications

    Creator:
    Christi, Arpit M.
    Abstract:
    Building software systems that adapt to the changing environment is challenging. Developers cannot anticipate all the changes in advance, and even if they could, the effort required to handle such situations is too onerous for practical purposes. Self Adaptive Software (SAS) adapts itself as per changing environment. The area of...
    Resource Type:
    Dissertation

  • 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...
    Resource Type:
    Dissertation