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Filtering by: Creator Welter, Stephen C. Remove constraint Creator: Welter, Stephen C. License All rights reserved Remove constraint License: All rights reserved Subject Machine learning Remove constraint Subject: Machine learning

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  • Classification and Analysis of Nucleotide - Nucleotide Interactions in RNA

    Creator:
    Rouches, Mason
    Abstract:
    Base-pairing interaction are the fundamental blocks of an RNA structure. With increased ability to determine the structure of RNA molecules, an accurate and informative way of classifying these interactions would help to study RNA structure at many levels. Apart from the well-known complementary base pairs and wobble pairs, other interactions...
    Resource Type:
    Honors College Thesis
    Full Text:
    _____________________________________________________________________ Stephen Ramsey, Committee Member, representing the Department of Biomedical Sciences and the

  • Object detection in biological images using a search-based framework

    Creator:
    Lam, Michael
    Abstract:
    This thesis addresses a basic problem in computer vision, that of semantic labeling of images. Our work is aimed at object detection in biological images for evolutionary biology research. In particular, our goal is to detect nematocysts in Scanning Electron Microscope (SEM) images. This biological domain presents challenges for existing...
    Resource Type:
    Masters Thesis
    Full Text:
    candidate labelings, and then applies a cost function (C) to select the best- scoring prediction among the

  • Spatial and Temporal Dynamics of Broad-scale Predictive Models : Influences of Scale

    Creator:
    Hooper, Samuel
    Abstract:
    Developing accurate predictive distribution models requires adequately representing relevant spatial and temporal scales, as these scales are ultimately reflective of the relationships between distributions and influential environmental conditions. In this research, we considered both spatial and temporal scale and the influence each has on predicting broad-scale distributions of two disparate...
    Resource Type:
    Masters Thesis
    Full Text:
    McCracken, and Dan Stephen who made up a fun and supportive Geography cohort. I am particularly grateful

  • Representationally Robust and Scalable Learning over Relational Databases

    Creator:
    Picado Leiva, Jose Manuel
    Abstract:
    Learning novel concepts from relational databases is an important problem with applications in several disciplines, such as data management, natural language processing, and bioinformatics. For a learning algorithm to be effective, the input data should be clean and in some desired representation. However, real-world data is usually heterogeneous – the...
    Resource Type:
    Dissertation
    Full Text:
    wrangling with robust learning algorithms. c©Copyright by Jose Manuel Picado Leiva May 28, 2019 All

  • Improving automated email tagging with implicit feedback

    Creator:
    Sorower, Mohammad Shahed
    Abstract:
    Machine learning systems are generally trained offline using ground truth data that has been labeled by experts. However, these batch training methods are not a good fit for many applications, especially in the cases where complete ground truth data is not available for offline training. In addition, batch methods do...
    Resource Type:
    Dissertation
    Full Text:
    to greatly reduce the number of clicks required to perform these tasks. c©Copyright by Mohammad S

  • Toward end-user debugging of machine-learned programs

    Creator:
    Kulesza, Todd
    Abstract:
    The results of a machine learning from user behavior can be thought of as a program, and like all programs, it may need to be debugged. Providing ways for the user to debug it matters because without the ability to fix errors, users may find that the learned program’s errors...
    Resource Type:
    Masters Thesis
    Full Text:
    and Stephen Perona worked with Dr. Wong to develop the machine learning component that was involved

  • Pixel- and Frame-level Video Labeling using Spatial and Temporal Convolutional Networks

    Creator:
    Lei, Peng
    Abstract:
    This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
    Resource Type:
    Dissertation
    Full Text:
    the time of our evaluation. c©Copyright by Peng Lei December 7, 2018 All Rights Reserved Pixel

  • Learning cost-sensitive diagnostic policies from data

    Creator:
    Zubek, Valentina Bayer
    Abstract:
    In its simplest form, the process of diagnosis is a decision-making process in which the diagnostician performs a sequence of tests culminating in a diagnostic decision. For example, a physician might perform a series of simple measurements (body tem- perature, weight, etc.) and laboratory measurements (white blood count, CT scan,...
    Resource Type:
    Dissertation
    Full Text:
    diagnostic policies that seek to minimize the expected total cost of diagnosis. c Copyright by Valentina

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation
    Full Text:
    best reported parsing results on the French Treebank. c©Copyright by James Henry Cross III December

  • Robust and Efficient Classification of Videos in the Wild

    Creator:
    Mahasseni, Behrooz
    Abstract:
    Recognizing human actions in videos is a long-standing problem in computer vision with a wide range of applications including video surveillance, content retrieval, and sports analysis. This thesis focuses on addressing efficiency and robustness of video classification in unconstrained real-world settings. The thesis work can be broadly divided into four...
    Resource Type:
    Dissertation
    Full Text:
    applications, and working in less sanitized settings. c©Copyright by Behrooz Mahasseni November 30, 2016