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  • Active learning with committees : an approach to efficient learning in text categorization using linear threshold algorithms

    Creator:
    Liere, Ray
    Abstract:
    We developed and investigated machine learning methods that require minimal preprocessing of the input data, use few training examples, run fast, and still obtain high levels of accuracy. Most approaches to designing machine learning programs are based on the supervised learning paradigm – training examples are chosen randomly and given...
    Resource Type:
    Dissertation
    Full Text:
    Professor, representing Computer Science Head of Department of Computer Science Dean of Graduate School I

  • Machine learning for cognitive networks : technology assessment and research challenges

    Creator:
    Oregon State University. Dept. of Computer Science, Dietterich, Thomas Glen, and Langley, Pat
    Abstract:
    The field of machine learning has made major strides over the last 20 years. This document summarizes the major problem formulations that the discipline has studied, then reviews three tasks in cognitive networking and briefly discusses how aspects of those tasks fit these formulations. After this, it discusses challenges for...
    Resource Type:
    Research Paper
    Full Text:
    Science Oregon State University Corvallis, OR 97331 Pat Langley Institute for the Study of Learning and

  • Learning diagnostic policies from examples by systematic search

    Creator:
    Oregon State University. Dept. of Computer Science and Zubek, Valentina Bayer
    Abstract:
    A diagnostic policy species what test to perform next based on the results of previous tests and when to stop and make a diagnosis. Cost-sensitive diagnostic policies perform tradeoffs between (a) the costs of tests and (b) the costs of misdiagnoses. An optimal diagnostic policy minimizes the expected total cost....
    Resource Type:
    Research Paper
    Full Text:
    Systematic Search Valentina Bayer�Zubek School of Electrical Engineering and Computer Science Oregon State

  • Machine learning for improving the quality of citizen science data

    Creator:
    Yu, Jun
    Abstract:
    Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
    Resource Type:
    Dissertation
    Full Text:
    Science Data AN ABSTRACT OF THE DISSERTATION OF Jun Yu for the degree of Doctor of Philosophy in

  • Emerging Technologies in Fisheries Science: A Transdisciplinary Report

    Creator:
    Firl, Alrik, Haven, Katlyn, and Newton, Samm
    Abstract:
    The Pacific Coast Groundfish Fishery harvests a diverse and large grouping of fishes, but it did not become heavily fished until around WWII. This makes the groundfish fishery a comparatively young fishery. Despite its youth, it is one of the largest and most lucrative fisheries in Oregon—with a current harvest...
    Resource Type:
    Research Paper
    Full Text:
    Humanities Funded by the National Science Foundation 2 Table of Contents I. Introduction

  • Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

    Creator:
    Hooper, Samuel
    Abstract:
    Developing accurate predictive distribution models requires adequately representing relevant spatial and temporal scales, as these scales are ultimately reflective of the relationships between distributions and influential environmental conditions. In this research, we considered both spatial and temporal scale and the influence each has on predicting broad-scale distributions of two disparate...
    Resource Type:
    Masters Thesis
    Full Text:
    , representing Geography Dean of the College of Earth, Ocean, and Atmospheric Sciences Dean

  • On the Role of Spatial Clustering Algorithms in Building Species Distribution Models from Community Science Data

    Creator:
    Roth, Mark
    Abstract:
    This paper discusses opportunities for developments in spatial clustering methods to help leverage broad scale community science data for building species distribution models (SDMs). SDMs are critical tools that inform the science and policy needed to mitigate the impacts of climate change on biodiversity. Community science data span spatial and...
    Resource Type:
    Capstone Project
    Full Text:
    partial fulfillment of the requirements for the degree of Master of Science in Computer Science

  • Image Based Crypto

    Creator:
    Basa, Gungor
    Abstract:
    The ability to create reproducible cryptographically secure keys from temporal environments (e.g., images) has the potential to be a contributor to effective cryptographic mechanisms. Due to the noisy nature of these environments, achieving this goal in a user friendly fashion is a very challenging task, especially since there exists a...
    Resource Type:
    Masters Thesis
    Full Text:
    Master of Science in Computer Science presented on December 2, 2016. Title: Image Based Crypto

  • Representations and algorithms for efficient inference in Bayesian networks

    Creator:
    Takikawa, Masami
    Abstract:
    Bayesian networks are used for building intelligent agents that act under uncertainty. They are a compact representation of agents' probabilistic knowledge. A Bayesian network can be viewed as representing a factorization of a full joint probability distribution into the multiplication of a set of conditional probability distributions. Independence of causal...
    Resource Type:
    Dissertation
    Full Text:
    Computer Science lair of Department of Computer Science Dean of Graduaf. School I understand that my

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation
    Full Text:
    the degree of Doctor of Philosophy in Computer Science presented on December 8, 2016. Title: Parsing