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Filtering by: Creator Guss, Thomas O. Remove constraint Creator: Guss, Thomas O. Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Exploitation and Mitigation of CPU Vulnerabilities

    Creator:
    Mestas, Phillip O., III
    Abstract:
    AMD SEV allows for the creation of fully encrypted virtual machines. This allows cloud computing tenants’ data to be secret to the cloud computing provider. However, it has been shown that the encryption scheme used by AMD can easily be broken. The attacker can create a copy of the virtual...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Phillip O. Mestas III for the

  • Comparing Chemical Kinetic Model Reduction Techniques Using pyMARS

    Creator:
    Mestas, Phillip O., III
    Abstract:
    Accurately modeling the chemistry of conventional and alternative liquid transportation fuels in combustion technology is vital to predicting important quantities such as the burning rate, heat release, and pollutant emissions. However, incorporating detailed chemical kinetic models into reactive-flow simulations poses a significant challenge due to the associated high computational expense...
    Resource Type:
    Honors College Thesis
    Full Text:
    Using pyMARS By Phillip O Mestas III A THESIS submitted to Oregon State University University

  • Relationship of pauses to problem solving events in mechanical design protocols

    Creator:
    Chamberlin, Martha J.
    Abstract:
    This thesis compares two methods for studying the problem-solving processes of mechanical design engineers. The first method, verbal protocol analysis, was applied by L. Stauffer to construct a problem-solving model of mechanical design. The second method, timing analysis, measures the time intervals separating drawing or speaking actions during the design...
    Resource Type:
    Masters Thesis
    Full Text:
    Events in Mechanical Design Protocols Abstract approved: Redacted for Privacy Thomas G. Dietterich

  • 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:
    : Improving Automated Email Tagging with Implicit Feedback Abstract approved: Thomas G. Dietterich Machine

  • Model-based approximation methods for reinforcement learning

    Creator:
    Wang, Xin
    Abstract:
    The thesis focuses on model-based approximation methods for reinforcement learning with large scale applications such as combinatorial optimization problems. First, the thesis proposes two new model-based methods to stablize the value–function approximation for reinforcement learning. The first one is the BFBP algorithm, a batch-like reinforcement learning process which iterates between...
    Resource Type:
    Dissertation
    Full Text:
    Methods for Reinforcement Learning. Abstract approved: Thomas G Dietterich The thesis focuses on model

  • Shrunken learning rates do not improve AdaBoost on benchmark datasets

    Creator:
    Forrest, Daniel L. K.
    Abstract:
    Recent work has shown that AdaBoost can be viewed as an algorithm that maximizes the margin on the training data via functional gradient descent. Under this interpretation, the weight computed by AdaBoost, for each hypothesis generated, can be viewed as a step size parameter in a gradient descent search. Friedman...
    Resource Type:
    Masters Thesis
    Full Text:
    Learning Rates Do Not Improve AdaBoost On Benchmark Datasets. Abstract approved: Thomas G. Dietterich

  • Learning functional descriptions from examples

    Creator:
    Flann, Nicholas S.
    Abstract:
    The task of inductive learning from examples places constraints on the representation of training instances and concepts. These constraints are different from, and often incompatible with, the constraints placed on the representation by the performance task. This incompatibility is severe when learning functional concepts and explains why previous researchers have...
    Resource Type:
    Masters Thesis
    Full Text:
    Abstract approve Thomas G. Dietterich. The task of inductive learning from examples places constraints on

  • Probabilistic models for quality control in environmental sensor networks

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Networks of distributed, remote sensors are providing ecological scientists with a view of our environment that is unprecedented in detail. However, these networks are subject to harsh conditions, which lead to malfunctions in individual sensors and failures in network communications. This behavior manifests as corrupt or missing measurements in the...
    Resource Type:
    Dissertation
    Full Text:
    : Probabilistic Models for Quality Control in Environmental Sensor Networks Abstract approved: Thomas G

  • Correct abstraction in counter-planning : a knowledge compilation approach

    Creator:
    Flann, Nicholas S.
    Abstract:
    Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach...
    Resource Type:
    Dissertation
    Full Text:
    1992. Approved: Redacted for Privacy Thomas G. Dietterich Redacted for Privacy Head of

  • Activity recognition in desktop environments

    Creator:
    Shen, Jianqiang
    Abstract:
    Knowledge workers are struggling in the information flood. There is a growing interest in intelligent desktop environments that help knowledge workers organize their daily life. Intelligent desktop environments allow the desktop user to define a set of “activities” that characterize the user’s desktop work. These environments then attempt to identify...
    Resource Type:
    Dissertation
    Full Text:
    Recognition in Desktop Environments Abstract approved: Thomas G. Dietterich Knowledge workers are