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Filtering by: Creator Southall, Brandon L. Remove constraint Creator: Southall, Brandon L. Degree Field Computer Science Remove constraint Degree Field: Computer Science Resource Type Dissertation Remove constraint Resource Type: Dissertation

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  • 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
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Matthew L

  • Meeting End-to-End Deadlines in Real-Time Networks Using Software Defined Networking (SDN)

    Creator:
    Almahdi, Rafid M.
    Abstract:
    Network flows in Real-Time (RT) systems need to meet stringent end-to-end deadlines in order for such systems to operate safely and reliably. Today, such systems use custom or domain specific network system designs to meet end-to-end deadlines and other constraints of real-time flows. In this work we explore the design...
    Resource Type:
    Dissertation
    Full Text:
    feedback on the main ideas of this work. Lastly, thanks to Brandon Ellis for programming and writing

  • 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:
    precisely, it tends to minimize L∞. Therefore, it uses the sign of gradient of loss function as follows

  • Empowering End Users to Mitigate Privacy and Security Risks in Smart-Home Trigger-Action Apps

    Creator:
    Saeidi, Mahsa
    Abstract:
    Many home users nowadays use various smart devices to improve the efficiency and convenience of their home environments. Trigger-action platforms such as “If-This-Then-That” (IFTTT) enable end users to connect different smart devices and services using simple apps to control these devices and automate the tasks (e.g., if the camera detects...
    Resource Type:
    Dissertation
    Full Text:
    collaborators, McKenzie Calvert, Audrey Au, Turgay Caglar, Brandon Ellis, and Marjan Adeli. I would also thank

  • Deep Convolutional Network on Point Clouds for 3D Scene Understanding

    Creator:
    Wu, Wenxuan
    Abstract:
    As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
    Resource Type:
    Dissertation
    Full Text:
    level l is concatenated with the upsampled feature from level l+ 1, which contains feature with a

  • Usable and Scalable Querying of Scientific Datasets

    Creator:
    McCamish, Benjamin J.
    Abstract:
    Scientists and engineers have to analyze and query multiple large databases. Analysis over databases created by phasor measurement units can provide insight into the health of the grid, thereby improving control over operations. Realizing this data-driven control, however, requires validating, processing and storing massive amounts of PMU data efficiently, which...
    Resource Type:
    Dissertation
    Full Text:
    quality of all the work presented in this thesis: Parisa, Yods, Jose, Rich, Brandon, Scott, Asher, Mike

  • Algorithms for massive biological datasets

    Creator:
    Bryant, Douglas W. (Douglas Wesley)
    Abstract:
    Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
    Resource Type:
    Dissertation

  • Designing Diversity and Inclusion Processes and Tools for Sustainable Open Source

    Creator:
    Guizani, Mariam
    Abstract:
    Over time, Open Source Software (OSS) has become indispensable in the creation and upkeep of software products, serving as the fundamental building block for widely used solutions in our daily lives, including applications that enable communication, entertainment, and productivity. A sustainable OSS ecosystem is one that attracts and retains a...
    Resource Type:
    Dissertation

  • 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

  • Exploratory Study to Uncover Student Mental Models of Singly Linked Lists in the C Programming Language

    Creator:
    Almadhoun, Eman
    Abstract:
    In computer science, learning abstract fundamental programming concepts requiring students to understand memory management can be very difficult and lead to misunderstandings that carry on into advanced topics. This is especially true in data structures with abstract data types. Understanding how novice students think and reason about data structures is...
    Resource Type:
    Dissertation