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Filtering by: Creator Mote, Don C. (Don Carlos) Remove constraint Creator: Mote, Don C. (Don Carlos) Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • An Investigation of the Effects of Merge Conflicts on Collaborative Software Development

    Creator:
    Brindescu, Caius
    Abstract:
    Merge conflicts have long plagued software development. With larger and more dispersed teams comes greater risk of developers working on the same code at the same time. While merge conflicts are known to be painful, their exact impact on software is still largely unknown. Are merge conflicts an isolated problem,...
    Resource Type:
    Dissertation
    Full Text:
    Sarma Carlos Jensen Merge conflicts have long plagued software development. With larger and more

  • 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:
    studies to ensure that they are effective and helpful. c©Copyright by Chris Chambers July 10, 2014

  • Interactive visualization of diversity in multivariate data sets unified across fields of study

    Creator:
    Pham, Tuan N. T.
    Abstract:
    The study of the diversity of multivariate objects shares common characteristics across disciplines, including ecology and organizational management. Nevertheless, experts in these two disciplines have adopted somewhat separate diversity concepts and analysis techniques, limiting the ability of potentially sharing and cross comparing these concerns. Moreover, while complex diversity data may...
    Resource Type:
    Dissertation
    Full Text:
    and refined in empirical user studies involving human participants and subject-matter experts. c

  • Developing a 2D Cross-section Training Strategy for 3D Volume Segmentation by Analyzing Human Perception and Cognitive Tasks

    Creator:
    Sanandaji, Anahita
    Abstract:
    3D volume segmentation is a fundamental process in many scientific and medical applications. Producing accurate segmentations, in an efficient way, is challenging, in part due to low imaging data quality (e.g., noise and low image resolution), and ambiguity in the data that can only be resolved with higher-level knowledge of...
    Resource Type:
    Dissertation
    Full Text:
    accurate 3D volume segmentation. c©Copyright by Anahita Sanandaji June 8, 2018 All Rights Reserved

  • Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

    Creator:
    Li, Yunfan
    Abstract:
    The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
    Resource Type:
    Dissertation
    Full Text:
    silicon interposer-based throughput processors, then utilize Monte Carlo Tree Search model (MCTS) to

  • ScaleIO Storage Driver: A Template Driver for CoprHD

    Creator:
    Shujin, Wu and Wu, Shujin
    Abstract:
    CoprHD is an open source software-defined storage and API platform which creates an abstraction layer over multi-vendor heterogeneous storage systems. It offers the ability to discover, pool and automate the management of the storage ecosystem with the help of storage drivers establishing connections between CoprHD and storage systems. On the...
    Resource Type:
    Capstone Project
    Full Text:
    Schoeb, Don Deel, Carlos Pratt, Chris Li- onetti, and Doug Voigt. Software defined storage, Jan 2015. [3

  • Multi-criteria average reward reinforcement learning

    Creator:
    Natarajan, Sriraam
    Abstract:
    Reinforcement learning (RL) is the study of systems that learn from interaction with their environment. The current framework of Reinforcement Learning is based on receiving scalar rewards, which the agent aims to maximize. But in many real world situations, tradeoffs must be made among multiple objectives. This necessitates the use...
    Resource Type:
    Masters Thesis
    Full Text:
    reinforcement learning techniques. Consider the fact that these weights can vary with time. One day the don

  • Uncertainty in Deep Learning with Implicit Neural Networks

    Creator:
    Ratzlaff, Neale
    Abstract:
    The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
    Resource Type:
    Dissertation
    Full Text:
    Monte Carlo . . . . . . . . . . . . . . . . . . . . . . 9 2.1.2 Variational Inference

  • 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:
    . c©Copyright by Béatrice Moissinac October 11, 2019 All Rights Reserved Computing Resource Usage

  • Machine Learning Techniques to Model Species Interactions and Distributions Under Imperfect Detection

    Creator:
    Seo, Eugene
    Abstract:
    Ecological domains seeking to understand the environment and the behavior of species have received little attention in machine learning (ML), despite the fact that environmental changes have a significant impact on humans as well as ecosystems. Some ecological problems can be formulated similarly to other common ML applications, but there...
    Resource Type:
    Dissertation
    Full Text:
    Analysis in Latent Spaces . . . . . . . . . . . . . . . . . . 136 C Proof of Lemma 1