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Filtering by: Creator Parra, Gabriel I. Remove constraint Creator: Parra, Gabriel I. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Efficient Oblivious Access to Trees

    Creator:
    Hackebeil, Gabriel A.
    Abstract:
    The outsourcing of data storage and related infrastructure to third-party services in the cloud is a trend that has gained considerable momentum in the last decade due to the savings it affords companies in both capital and operational costs. Although encryption can alleviate some of the privacy concerns associated with...
    Resource Type:
    Masters Thesis
    Full Text:
    request. Gabriel A. Hackebeil, Author ACKNOWLEDGEMENTS First and foremost, I would like to thank my

  • On Avoiding Power-Seeking by Artificial Intelligence

    Creator:
    Turner, Alexander M.
    Abstract:
    We do not know how to align a very intelligent AI agent's behavior with human interests. I investigate whether—absent a full solution to this AI alignment problem—we can build smart {\ai} agents which have limited impact on the world, and which do not autonomously seek power. In this thesis, I...
    Resource Type:
    Dissertation
    Full Text:
    not know how to align a very intelligent ai agent’s behavior with human interests. I investigate

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation
    Full Text:
    using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal

  • Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

    Creator:
    Khorram, Saeed
    Abstract:
    The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
    Resource Type:
    Dissertation
    Full Text:
    family of attribution maps called Integrated Gradient-Optimized Saliency Maps (I-GOS) that generate

  • Theory and Implementation of a Variational Database Management System

    Creator:
    Ataei, Parisa S.
    Abstract:
    In this thesis, I present the variational database management system, a formal framework and its implementation for representing variation in relational databases and managing variational information needs. A variational database is intended to support any kind of variation in a database. Specific kinds of variation in databases have already been...
    Resource Type:
    Dissertation
    Full Text:
    , I present the variational database management system, a formal framework and its implementation for

  • Information-theoretic Approach to Design and Evaluate Privacy-preserving and Fair Frameworks for Continuous High-dimensional Data

    Creator:
    Alsulaimawi, Zahir Ahmed Hussein
    Abstract:
    Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them. Further, there have been concerns about the possibility of bias and discrimination in predictive applications. In order to address these issues, we propose an...
    Resource Type:
    Dissertation
    Full Text:
    of the Graduate School I understand that my dissertation will become part of the permanent

  • Improving automated email tagging with implicit feedback

    Creator:
    Sorower, Mohammad Shahed
    Abstract:
    Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
    Resource Type:
    Dissertation
    Full Text:
    incorporating implicit feedback into the TAPE email tag predictor. These algorithms are then evaluated using (i

  • Newcomers’ Barriers. . . Is That All? An Analysis of Mentors’ and Newcomers’ Barriers in OSS Projects

    Creator:
    Balali, Sogol
    Abstract:
    Newcomers’ seamless onboarding is important for open collaboration communi- ties, particularly those that leverage outsiders’ contributions to remain sustainable. Nevertheless, previous work shows that OSS newcomers often face several barriers to contribute, which lead them to lose motivation and even give up on contributing. A well-known way to help newcomers...
    Resource Type:
    Masters Thesis
    Full Text:
    School I understand that my thesis will become part of the permanent collection of Oregon State

  • 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:
    Computer Science Dean of the Graduate School I understand that my dissertation will become part of the

  • Identifying and Removing On-chip Network Bottleneck in Throughput Processors

    Creator:
    Li, Yunfan
    Abstract:
    The high level of parallelism in throughput processors such as GPGPUs has resulted in significantly changed on-chip data traffic behaviors. This demands new research to identify and address the limiting factors of networks-on-chip (NoCs) in the context of throughput processors. In this work, we first quantitatively analyze the performance of...
    Resource Type:
    Masters Thesis
    Full Text:
    the Graduate School I understand that my thesis will become part of the permanent collection of