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Filtering by: Creator Brenner, Gregory John Remove constraint Creator: Brenner, Gregory John Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Visualization and design systems for road infrastructure

    Creator:
    Esch, Gregory
    Abstract:
    Transportation infrastructure provides a vital service for the functionality of a city. The efficient design of road networks poses an interesting topic in computer science for digital content developers. For civil engineers, the visualization of analysis results on infrastructure both efficiently and intuitively is crucial. The following contributions are made...
    Resource Type:
    Masters Thesis
    Full Text:
    AN ABSTRACT OF THE THESIS OF Gregory Esch for the degree of Master

  • A comparison of box-cox and additive exponential models to estimate the depreciation of farm machinery

    Creator:
    Wu, Jing
    Abstract:
    Farm machinery continues to increase in its importance to the agricultural sector. Depreciation, the decline in value of a durable asset over time, represents one of the largest costs of agricultural production. The general objectives of this study were to update and expand the number of Remaining Value (RV) functions...
    Resource Type:
    Masters Thesis
    Full Text:
    privacy ACKNOWLEDGMENTS First of all, I would like to thank my major professor, Dr. Gregory Perry, to

  • 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

  • Fine-Grained Object Recognition Under Limited Training Data

    Creator:
    Lam, Michael Q.
    Abstract:
    This dissertation addresses object recognition in challenging settings, where distinct object classes are visually very similar (e.g., species of birds and insects) and/or access to training examples of object classes is limited (e.g., due to the associated high costs of data annotation). In this dissertation, we present a variety of...
    Resource Type:
    Dissertation

  • 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

  • Species Distribution Modeling of Citizen Science Data as A Classification Problem with Class-Conditional Label Noise

    Creator:
    He, Liqiang
    Abstract:
    Species distribution models (SDM), which quantify the correlation between the distribution of a species and environmental factors, are increasingly used to map and monitor animal and plant distributions in the context of awareness of environmental change and its ecological consequence. For perfect data, this is a straightforward classification problem from...
    Resource Type:
    Masters Thesis
    Full Text:
    thank my thesis committee: Prof. Thomas G. Dietterish, Prof. Amir Nayyeri and Prof. John P. Bolte, for

  • 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

  • Algorithms for massive biological datasets

    Creator:
    Bryant, Douglas W. (Douglas Wesley)
    Abstract:
    Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
    Resource Type:
    Dissertation

  • Interpretable Machine Learning: Applications in Biology and Genomics

    Creator:
    Danaee, Padideh
    Abstract:
    Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
    Resource Type:
    Dissertation

  • Learning and Improving Policies for Probabilistic Planning Problems

    Creator:
    Issakkimuthu, Murugeswari
    Abstract:
    In this work, we study the problem of learning and improving policies for probabilistic planning problems. In the first part, we train neural network policies for probabilistic planning problems modeled as factored Markov decision problems. The objective is to train problem-specific neural networks via supervised learning to imitate the action...
    Resource Type:
    Dissertation