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Filtering by: Creator Gabriel, John T. Remove constraint Creator: Gabriel, John T. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad Non-Academic Affiliation Oregon State University. Graduate School Remove constraint Non-Academic Affiliation: Oregon State University. Graduate School

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  • Protein secondary structure prediction using conditional random fields and profiles

    Creator:
    Shen, Rongkun
    Abstract:
    Protein secondary structure prediction plays a pivotal role in predicting protein folding in three-dimensions. Its task is to assign each residue one of the three secondary structure classes helix, strand, or random coil. This is an instance of the problem of sequential supervised learning in machine learning. This thesis describes...
    Resource Type:
    Masters Thesis
    Full Text:
    recursion is ( , ) 1k Tβ = ' ' ( , ) exp ( , ( )) ( ', )1 1 k i k k i F k w X k iα β

  • Incorporating User Feedback into Machine Learning Systems

    Creator:
    Das, Shubhomoy
    Abstract:
    Although machine learning systems are often effective in real-world applications, there are situations in which they can be even better when provided with some degree of end user feedback. This is especially true when the machine learning system needs to customize itself to the end user's preferences, such as in...
    Resource Type:
    Dissertation
    Full Text:
    systems. I am grateful that Dr. John Dilles volunteered to serve as the Graduate Council Representative

  • Simulator-Defined MDP Planning with Applications in Natural Resource Management

    Creator:
    Alkaee Taleghan, Majid
    Abstract:
    This work is inspired by problems in natural resource management centered on the challenge of invasive species. Computing optimal management policies for maintaining ecosystem sustainable is challenging. Many ecosystem management problems can be formulated as MDP (Markov Decision Process) planning problems. In a simulator-defined MDP, the Markovian dynamics and rewards...
    Resource Type:
    Dissertation
    Full Text:
    Hutchinson, and John Dilles, for their constructive comments on my research. I would like to acknowledge all

  • Machine learning methods for public policy : simulation, optimization, and visualization

    Creator:
    McGregor, Sean
    Abstract:
    Society faces many complex management problems, particularly in the area of shared public resources such as ecosystems. Existing decision making processes are often guided by personal experience and political ideology rather than state-of-the-art scientific understanding. This dissertation envisions a future in which multiple stakeholders are provided with computational tools for...
    Resource Type:
    Dissertation
    Full Text:
    , Ronald Metoyer, Prasad Tadepalli, Margaret Burnett, and John Bolte for the time and effort they

  • Advanced separation of concerns and the compatibility of aspect-orientation

    Creator:
    Dechow, Doug
    Abstract:
    The appropriate separation of concerns is a fundamental engineering principle. A concern, for software developers, is that which must be represented by code in a program; by extension, separation of concerns is the ability to represent a single concern in a single appropriate programming language construct. Advanced separation of concerns...
    Resource Type:
    Dissertation
    Full Text:
    and suggestions for which the author is grateful. With the help of Prof. John Dooley, whose

  • The density signature

    Creator:
    Migler-VonDollen, Theresa
    Abstract:
    In real networks, identifying dense regions is of great importance. For example, in a network that represents academic collaboration, authors within the densest component of the graph tend to be the most prolific. Dense subgraphs often identify communities in social networks. And dense subgraphs can be used to discover regulatory...
    Resource Type:
    Dissertation
    Full Text:
    partner in my academic and personal adventures. You’re the tops. And to Gabriel, thank you for your

  • A SAT-based planning framework for optimizing resource production

    Creator:
    Ventura, Christopher
    Abstract:
    Domain-independent automated planning is concerned with computing a sequence of actions that can transform an initial state into a desired goal state. Resource production domains form an interesting class of such problems, in that they typically require reasoning about concurrent durative-actions with continuous effects while minimizing some cost function. Although...
    Resource Type:
    Masters Thesis
    Full Text:
    the capacity. Furthermore, the ‘#t’ keyword is a term denoting that the corresponding change is

  • Modeling and dynamics analysis of P2P networks based on evolutionary games

    Creator:
    Cho, Seungyun
    Abstract:
    Since free riders in P2P network reduce the system's performance, how to maintain and encourage the nodes' cooperation is an important aspect of P2P related research. In this thesis, a P2P system is modeled based on two games: stag hunt game and snowdrift game. To relate the model to the...
    Resource Type:
    Masters Thesis
    Full Text:
    ......................................................................................................... 22 TABLE OF CONTENTS(Continued) Page 4.5.1 R>T, and S>P

  • 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:
    ., keeping track of fantasy football results). We are also interested in design- 11 ac t i v i t y a d v

  • 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:
    . However, these batch training methods are not a good �t for many applications, especially in the cases