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Filtering by: Creator Hazou, Irene A Remove constraint Creator: Hazou, Irene A Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • A conceptual framework for web-based collaborative design

    Creator:
    Gottfried, Shikha Ghosh
    Abstract:
    Although much effort has been invested to build applications that support group work, collaborative applications have not found easy success. The cost of adopting and maintaining collaborative applications has prevented their widespread use, especially among small distributed groups. Application developers have had difficulties recognizing the extra effort required by groups...
    Resource Type:
    Masters Thesis
    Full Text:
    A Conceptual Framework for Web-based Collaborative Design AN

  • Spreadsheet Explanation Through Table Abstraction

    Creator:
    Dan, Mihai
    Abstract:
    Spreadsheets are a pervasive technology throughout personal and industrial use. Often times, the user is not the author, contributing to a lack of understanding of the purpose and functionality of a spreadsheet. Furthermore, the lack of understanding is a major reason for mistakes in the use and maintenance of spreadsheets....
    Resource Type:
    Masters Thesis
    Full Text:
    Through Table Abstraction Abstract approved: Martin Erwig Spreadsheets are a pervasive technology

  • Poisoning machine learning models to increase membership inference risks

    Creator:
    Le, Hoang
    Abstract:
    Deep learning is now being utilized widely in applications where sensitive data is being used for model training, for example, in health care. In this scenario, any data leakage will cause privacy concerns to whose data records are used to train the model. An attacker can actively cause privacy leakage...
    Resource Type:
    Masters Thesis
    Full Text:
    inference (MI) attack, which aims to infer if a data point belongs to the training set of the deep

  • Anomaly Detection and Probabilistic Diagnosis for Automated Data Quality Control

    Creator:
    Zemicheal, Tadesse H.
    Abstract:
    Advances in sensor technology are greatly expanding the range of quantities that can be measured while simultaneously reducing the cost. However, deployed sensors drift out of calibration and fail, so every sensor network requires quality control procedures to promptly detect these failures. To address these problems, we propose a two-level...
    Resource Type:
    Dissertation
    Full Text:
    failures. To address these problems, we propose a two-level architecture, SENSOR-DX, for automated quality

  • Newcomers’ Barriers. . . Is That All? An Analysis of Mentors’ and Newcomers’ Barriers in OSS Projects

    Creator:
    Balali, Sogol
    Abstract:
    Newcomers’ seamless onboarding is important for open collaboration communi- ties, particularly those that leverage outsiders’ contributions to remain sustainable. Nevertheless, previous work shows that OSS newcomers often face several barriers to contribute, which lead them to lose motivation and even give up on contributing. A well-known way to help newcomers...
    Resource Type:
    Masters Thesis
    Full Text:
    and even give up on contributing. A well-known way to help newcomers overcome initial contribution

  • Investigating Latent State and Uncertainty Representations in Reinforcement Learning

    Creator:
    Koul, Anurag
    Abstract:
    Learning latent space representations of high-dimensional world states has been at the core of recent rapid growth in reinforcement learning(RL). At the same time, RL algo- rithms have suffered from ignored uncertainties in the predicted estimates of model-free or model-based methods. In our work, we investigate both of these aspects...
    Resource Type:
    Dissertation
    Full Text:
    to their use of continuous- valued memory vectors and observation features. We introduced a new

  • Convergence Analysis Framework for Fixed-Point Algorithms in Machine Learning and Signal Processing

    Creator:
    Vu, Trung
    Abstract:
    Iterative algorithms are simple yet efficient in solving large-scale optimization problems in practice. With a surge in the amount of data in past decades, these methods have become increasingly important in many application areas including matrix/tensor recovery, deep learning, data mining, and reinforcement learning. To optimize or improve iterative algorithms,...
    Resource Type:
    Dissertation
    Full Text:
    - lems in practice. With a surge in the amount of data in past decades, these meth- ods have become

  • Design of efficient constant weight codes

    Creator:
    Tallini, Luca
    Abstract:
    In a constant weight code, each code word contains a constant number of 1's. If this number is equal to half the length of the code word then the code is called balanced. These codes find many applications in computer and communication systems noise reduction in VLSI systems, fault masking...
    Resource Type:
    Dissertation
    Full Text:
    In a constant weight code, each code word contains a constant number of l's. If this number is

  • Helping end-user programmers find and fix performance problems in visual code

    Creator:
    Chambers, Chris
    Abstract:
    End-user programmers often struggle to create programs that run quickly and effectively, which can be a major deterrent in completing their tasks as desired. Current research has primarily focused on catching user mistakes, such as errors or misused formulas. However, end users deal with issues other than just correctness. In...
    Resource Type:
    Dissertation
    Full Text:
    often struggle to create programs that run quickly and effec­ tively, which can be a major deterrent in

  • 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:
    categorization is to assign each document in a collection to appropriate categories. Most existing text