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Filtering by: Creator Morrison, H. Frank Remove constraint Creator: Morrison, H. Frank Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan

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  • Predicting activity type from accelerometer data

    Creator:
    Zheng, Yonglei
    Abstract:
    The study of physical activity is important in improving people’s health as it can help people understand the relationship between physical activity and health. Accelerometers, due to its small size, low cost, convenience and its ability to provide objective information about the frequency, intensity, and duration of physical activity, has...
    Resource Type:
    Masters Thesis
    Full Text:
    would like to thank my entire committee, Weng-Keen Wong, Stewart Trost, Alan Fern and Kenneth H. Funk

  • Efficient Algorithms for Robust Spatiotemporal Data Analysis

    Creator:
    Moore, Travis W.
    Abstract:
    Many large-scale data analysis applications involve data that can vary over both time and space. Often the primary goal of analyzing spatiotemporal data is identifying trends, movements, and sudden changes with respect to time, location, or both. This can include a variety of applications in economics (housing prices, unemployment, job...
    Resource Type:
    Dissertation
    Full Text:
    , Max Larrivee, Jeffrey Oliver and Jeremy Kerr) and eBird (Daniel Fink, Chris Wood, and Frank La Sorte

  • Network Coding, Random Matrices, and Their Applications to Communication Systems

    Creator:
    Nguyen-Huu, Duong
    Abstract:
    In this work, we study network coding technique, its relation to random matrices, and their applications to communication systems. The dissertation consists of three main contributions. First, we propose efficient algorithms for data synchronization via a broadcast channel using random network coding. Second, we study the resiliency of network coding...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . 81 5.10 Average optimal value versus k (rank of topology matrix H) . . . . . . . . 85 5.11 Average

  • 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:
    GF C J L I N M D H E A B K GF C J L I N M D H E A B K GF C J L I N M D H E

  • Structured learning with latent variables : theory and algorithms

    Creator:
    Zhao, Kai
    Abstract:
    Most tasks in natural language processing (NLP) try to map structured input (e.g., sentence or word sequence) to some form of structured output (tag sequence, parse tree, semantic graph, translated/paraphrased/compressed sentence), a problem known as “structured prediction”. While various learning algorithms such as the perceptron, maximum entropy, and expectation-maximization have...
    Resource Type:
    Dissertation

  • Efficient Incremental Panorama Reconstruction from Multiple Videos

    Creator:
    Feng, Zhongyuan
    Abstract:
    Constructing a panorama from a set of videos is a long-standing problem in computer vision. A panorama represents an enhanced still-image representation of an entire scene captured in a set of videos, where each video shows only a part of the scene. Importantly, a panorama shows only the scene background,...
    Resource Type:
    Capstone Project
    Full Text:
    +H23 (3.3) Re-writing the above equations,3 axh = 0 ayh = 0 h = (h1,h2,h3)T (3.4) 2We use

  • Action Segmentation with Limited Supervision

    Creator:
    Li, Jun
    Abstract:
    In this dissertation, we address action segmentation in videos under limited supervision. The goal of action segmentation is to predict an action class for each frame of a video. The limited supervision means ground truth labels of video frames are not available in training. We focus on three types of...
    Resource Type:
    Dissertation
    Full Text:
    …… 𝑏𝑖−1 𝑏𝑖 𝑏𝑖+1 𝑏𝑖+2 …… … … … … 𝜋1 𝜋2 … 𝜋𝑃 V al id p at h s In va lid p at h s

  • Applying machine learning for prediction, recommendation, and integration

    Creator:
    Bao, Xinlong
    Abstract:
    This dissertation explores the idea of applying machine learning technologies to help computer users find information and better organize electronic resources, by presenting the research work conducted in the following three applications: FolderPredictor, Stacking Recommendation Engines, and Integrating Learning and Reasoning. FolderPredictor is an intelligent desktop software tool that helps...
    Resource Type:
    Dissertation
    Full Text:
    expected number of clicks required to reach the user’s target folder. The candidate set H here consists of

  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    ; and 3) There is a bound on the total number of experiments, n, and a time horizon, h, by which point

  • Active Learning from Examples, Queries and Explanations

    Creator:
    Hamidi-Haines, Mandana
    Abstract:
    Humans are remarkably efficient in learning by interacting with other people and observing their behavior. Children learn by watching their parents’ actions and mimic their behavior. When they are not sure about their parents demonstration, they communicate with them, ask questions, and learn from their feedback. On the other hand,...
    Resource Type:
    Dissertation
    Full Text:
    Blackbird, (d) Red-winged Blackbird, (e) Northern Fulmar, (f) Green Jay, (g) Mallard, (h) Black Tern, (i