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Filtering by: Contributor Färe, Rolf G. Remove constraint Contributor: Färe, Rolf G. Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • A probabilistic model for anomaly detection in remote sensor streams

    Creator:
    Dereszynski, Ethan W.
    Abstract:
    Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access. Unfortunately, sensor data streams exhibit many kinds of errors ranging from corrupt communications to partial...
    Resource Type:
    Masters Thesis
    Full Text:
    Remote Sensor Streams Abstract approved: Thomas G. Dietterich Remote sensors are becoming the standard

  • Code generation in the Oregon speedcode universe

    Creator:
    Armstrong, James R. (James Russel)
    Abstract:
    The purpose of this project was to create a code generating software tool, which is one section of the Oregon SpeedCode Universe. The Code Generator automatically generates compilable source code to form working Macintosh applications. This source code provides a prototype for the actual final application. This is done with...
    Resource Type:
    Masters Thesis

  • 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:
    : Thomas G. Dietterich Advances in sensor technology are greatly expanding the range of quantities that

  • Machine Learning Methods for Computational Sustainability

    Creator:
    Liu, Liping
    Abstract:
    Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
    Resource Type:
    Dissertation
    Full Text:
    Methods for Computational Sustainability Abstract approved: Thomas G. Dietterich Maintaining the

  • 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

  • Individual Fairness Optimization in Machine Learning with Minimax Loss and an Abstain Option

    Creator:
    Behnoudfar, Ali
    Abstract:
    In this thesis, a new learning algorithm is introduced that is targeted towards individual fairness. In order to be individually fair, mispredictions need to be avoided as each such prediction means the learning algorithm was unfair towards some individual. Therefore, achieving individual fairness implies having a perfect classifier, which is...
    Resource Type:
    Masters Thesis
    Full Text:
    when the rejection option is taken. As shown in [27], the optimal classification rule g∗ : X 7→ ỹ is

  • Efficient Comparative Sequence Analysis Algorithms for RNA Conserved Structure and Region Detection

    Creator:
    Li, Sizhen
    Abstract:
    RNAs play important roles in multiple cellular processes, and many of their functions rely on folding to specific structures. To maintain their functions, secondary structures of RNA homologs are conserved across evolution. These conserved structures provide critical targets for diagnostics and therapeutics. Thus, there is a need for developing fast...
    Resource Type:
    Dissertation
    Full Text:
    three states {ALN, INS1, INS2 }, and each state emits a character pair (c1, c2) with values from {A, G

  • Constructive induction for improved learning of boolean functions

    Creator:
    Drake, Peter (Peter Dudey), 1970-
    Abstract:
    Supervised learning programs, such as decision tree learners and neural networks, often must learn Boolean functions. The concept being learned may not easily be expressed in terms of the atomic features given. Constructive induction automatically produces higher level features (combinations of the atomic features), which can improve learning performance. The...
    Resource Type:
    Masters Thesis
    Full Text:
    known, but not if any n -1 of them are known. Greedy methods such as decision trees fare particularly

  • Layered rendering model for human teeth

    Creator:
    Shetty, Sudarshanram
    Abstract:
    This study introduces a layered model for rendering human teeth. Human teeth exhibit complex light interaction due to their layered structure. While the lighting responses of teeth have been studied in the dental industry for the production of realistic looking dentures, to our knowledge this is the first study of...
    Resource Type:
    Masters Thesis
    Full Text:
    factor (g)[dimensionless] is a measure of light traveling in its intended path after scattering event. It

  • Linear-time Algorithms for RNA Folding: Partition Function, Stochastic Sampling and RNA-RNA Interaction

    Creator:
    Zhang, He
    Abstract:
    RNAs play important roles in the central dogma of molecular biology, and are involved in multiple biology processes such as chromatin modification, transcriptional interference and translation initiation. The functions of RNAs, especially non-coding RNAs, are highly related to its secondary structures, therefore computational methods for RNA structure prediction are of...
    Resource Type:
    Dissertation
    Full Text:
    studies focus on predicting secondary structure, the set of canonical base pairs in the structure (A-U, G