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Filtering by: Alternative title ssim Internal report no. 125 Remove constraint Alternative title ssim: Internal report no. 125 Committee Member Tadepalli, Prasad Remove constraint Committee Member: Tadepalli, Prasad

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  • Feedback-Based Random Test Generator for TSTL

    Creator:
    Kaneoka, Kazuki
    Abstract:
    Software testing is the process of evaluating the accuracy and performance of software, and automated software testing allows programmers to develop software more efficiently by decreasing testing costs. We compared two advanced random test generators, a Feedback-Directed Random Test Generator (FDR) and a Feedback-Controlled Random Test Generator (FCR), for an...
    Resource Type:
    Capstone Project
    Full Text:
    throughout my studies and research. There is no doubt that I would not have accomplished this achievement

  • Investigation of automatic construction of reactive controllers

    Creator:
    Westerberg, Caryl J.
    Abstract:
    In real-time control systems, the value of a control decision depends not only on the correctness of the decision but also on the time when that decision is available. Recent work in real-time decision making has used machine learning techniques to automatically construct reactive controllers, that is, controllers with little...
    Resource Type:
    Masters Thesis
    Full Text:
    automatically construct reactive controllers, that is, controllers with little or no internal state and low

  • The Ownership Monad

    Creator:
    McGirr, Michael G.
    Abstract:
    The Rust programming language is a systems programming language with a strong static type system. A central feature of Rust’s type system is its unique concept of “ownership”, which enables Rust to give a user safe, low-level control over resources without the overhead of garbage collection. In Haskell, most data...
    Resource Type:
    Capstone Project
    Full Text:
    mutable references and concurrency. This project report introduces the Ownership Monad, a monad that

  • 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:
    uninteresting to a user as the internal statistical model may not necessarily be aligned with the user’s

  • Shrunken learning rates do not improve AdaBoost on benchmark datasets

    Creator:
    Forrest, Daniel L. K.
    Abstract:
    Recent work has shown that AdaBoost can be viewed as an algorithm that maximizes the margin on the training data via functional gradient descent. Under this interpretation, the weight computed by AdaBoost, for each hypothesis generated, can be viewed as a step size parameter in a gradient descent search. Friedman...
    Resource Type:
    Masters Thesis
    Full Text:
    descent algorithm. For this report, we tested whether reduced learning rates can also improve

  • 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:
    thesis.dvi AN ABSTRACT OF THE PROJECT REPORT OF Zhongyuan

  • Adaptive Multiagent Traffic Management for Autonomous Robotic Systems

    Creator:
    Rebhuhn, Carrie
    Abstract:
    There is growing commercial interest in the use of unmanned aerial vehicles (UAVs) in urban environments, specifically for package delivery applications. However, the size, complexity and sheer numbers of expected UAVs makes conventional air traffic management that relies on human air traffic controllers infeasible. To enable UAVs to safely and...
    Resource Type:
    Dissertation
    Full Text:
    own individual internal cost-based planner to travel between locations. We then use neuro-evolution

  • A factoring approach for probabilistic inference in belief networks

    Creator:
    Li, Zhaoyu
    Abstract:
    Reasoning about any realistic domain always involves a degree of uncertainty. Probabilistic inference in belief networks is one effective way of reasoning under uncertainty. Efficiency is critical in applying this technique, and many researchers have been working on this topic. This thesis is the report of our research in this...
    Resource Type:
    Dissertation
    Full Text:
    been working on this topic. This thesis is the report of our research in this area. This thesis

  • Learning with Limited Labeled Data in Natural Language Processing

    Creator:
    Obeidat, Rasha
    Abstract:
    The advent of deep learning models leads to a substantial improvement in a wide range of NLP tasks, achieving state-of-art performances without any hand-crafted features. However, training deep models requires a massive amount of labeled data. Labeling new data as a new task or domain emerges consumes time and efforts...
    Resource Type:
    Dissertation
    Full Text:
    ] assume that no labeled data are available in the target domain, and use multiple source domain with

  • Computing Resource Usage as a Factor of Student Success

    Creator:
    Moissinac, Béatrice
    Abstract:
    Learning Analytics and other branches of Educational Research such as Computing Education Research (CER) implicitly assume that students, especially college students, have no barriers to access learning platforms or software packages. This assumption may be attributed to such pervasive beliefs such as "everyone has a device", or "everyone can access...
    Resource Type:
    Dissertation
    Full Text:
    Research (CER) implicitly assume that students, especially college students, have no barriers to access