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Filtering by: Creator Michael, Todd P. Remove constraint Creator: Michael, Todd P. Degree Field Computer Science Remove constraint Degree Field: Computer Science Degree Level Doctoral Remove constraint Degree Level: Doctoral

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  • Personalizing machine learning systems with explanatory debugging

    Creator:
    Kulesza, Todd
    Abstract:
    How can end users efficiently influence the predictions that machine learning systems make on their behalf? Traditional systems rely on users to provide examples of how they want the learning system to behave, but this is not always practical for the user, nor efficient for the learning system. This dissertation...
    Resource Type:
    Dissertation
    Full Text:
    Debugging AN ABSTRACT OF THE DISSERTATION OF Todd Kulesza for the degree of Doctor of Philosophy in

  • 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
    Full Text:
    : Algorithms for Massive Biological Datasets Abstract approved: Weng-Keen Wong Todd C. Mockler Within the

  • Understanding Software Development and Testing Practices

    Creator:
    Hilton, Michael
    Abstract:
    A bad software development process leads to wasted effort and inferior products. In order to improve a software process, it must be first understood. In this work I focus on understanding software processes. The first process we seek to understand is Continuous Integration (CI). CI systems automate the compilation, building,...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Michael Hilton for the

  • High-Dimensional Reinforcement Learning with Human Feedback

    Creator:
    Curran, William
    Abstract:
    State-of-the-art personal robots need to perform complex manipulation tasks to be viable in complex scenarios. However, many of these robots, like the PR2, use manipulators with high degrees of freedom. High degrees of freedom are desirable from a functionality standpoint, but make the learning task more difficult by adding a...
    Resource Type:
    Dissertation
    Full Text:
    ]. Reinforcement learning addresses the problem of finding an optimal policy, π∗(s, a) = P (a|s), that maximizes a

  • Incorporating and Learning Behavior Constraints for Sequential Decision Making

    Creator:
    Pinto, Jervis
    Abstract:
    Writing a program that performs well in a complex environment is a challenging task. In such problems, a method of deterministic programming combined with reinforcement learning (RL) can be helpful. However, current systems either force developers to encode knowledge in very specific forms (e.g., state-action features), or assume advanced RL...
    Resource Type:
    Dissertation
    Full Text:
    Constraints for Sequential Decision Making Abstract approved: Alan P. Fern Writing a program that performs

  • Characterizing Server Compromise: Resilience Models, Instantiations, and Impossibilities

    Creator:
    McQuoid, Ian M.
    Abstract:
    One of the pervasive problems arising in our modern, digital world surrounds data breaches where an adversary, through zero-day exploitations, phishing, or old-fashioned social engineering attacks, gains access to a service’s data stores. Our society increasingly relies on these cloud-based services for everything from our taxes to personal communication. As...
    Resource Type:
    Dissertation

  • New constructions and applications for homomorphic secret sharing and function secret sharing

    Creator:
    Singh, Jaspal
    Abstract:
    A secret sharing scheme allows a dealer to distribute a secret with a set of parties, such that only a certain subset of parties can collaborate and learn the shared secret. Traditional secret sharing schemes have been used as building blocks in various subdomains of cryptography. Recently, two new extensions...
    Resource Type:
    Dissertation
    Full Text:
    implicit in sparse-OT PSI [PRTY19]. . . . . . . . . . . . . . 156 5 (p, 1)-bFSS implicit in Chase-Miao PSI

  • Domain-Independent Planning for Markov Decision Processes with Factored State and Action Spaces

    Creator:
    Raghavan, Aswin
    Abstract:
    Markov Decision Processes (MDPs) are the de-facto formalism for studying sequential decision making problems with uncertainty, ranging from classical problems such as inventory control and path planning, to more complex problems such as reservoir control under rainfall uncertainty and emergency response optimization for fire and medical emergencies. Most prior research...
    Resource Type:
    Dissertation
    Full Text:
    pruning operator P(D,π) ≡ Pπ(D) for any ADD D and a policy constraint BDD π

  • High-performance data-parallel input/output

    Creator:
    Moore, Jason Andrew
    Abstract:
    Existing parallel file systems are proving inadequate in two important arenas: programmability and performance. Both of these inadequacies can largely be traced to the fact that nearly all parallel file systems evolved from Unix and rely on a Unix-oriented, single-stream, block-at-a-time approach to file I/O. This one-size-fits-all approach to parallel...
    Resource Type:
    Dissertation
    Full Text:
    - Michael J. Quinn Existing parallel file systems are proving inadequate in two important arenas

  • Analytical performance prediction of data-parallel programs

    Creator:
    Clement, Mark J.
    Resource Type:
    Dissertation
    Full Text:
    Programs ftAbstract approved- Michael J. Quinn A combination of static and dynamic performance