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Filtering by: Creator Payette, B. C. Remove constraint Creator: Payette, B. C. Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan Resource Type Dissertation Remove constraint Resource Type: Dissertation

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  • Deep Learning for Human and Biological Languages

    Creator:
    Hong, Junki
    Abstract:
    We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
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    Dissertation
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    or k B ea m 1 0 C h a rt P a rs in g Figure 2.3: Runtime plot of decoding the discourse

  • Weakly Supervised Learning for Activity Recognition from Time Series Data

    Creator:
    Guan, Xinze
    Abstract:
    The thesis focuses on activity recognition from sensor data, which has spurred a great deal of interest due to its impact on health care and security. Previous work on activity recognition from multivariate time series data has mainly applied supervised learning techniques which require a high degree of annotation effort...
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    Dissertation
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    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 B Complete Data Log-likelihood and Surrogate Objective . . . . . . . . . . . 99 C Expectation

  • Automatic Explanations of Computation Results with Value Decompositions and Dominating Sets

    Creator:
    Kumar, Prashant
    Abstract:
    In an increasingly computation-driven world, algorithms and mathematical models significantly impact decision making across various fields. To foster trust and understanding, it is crucial to provide users with clear and concise explanations of the reasoning behind the results produced by computational tools, especially when recommendations appear counterintuitive. Legal frameworks in...
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    Dissertation
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    two elements A and B as follows. δ(A, B) = {(c, x− y) | (c, x) ∈ φ(A) ∧ (c, y) ∈ φ(B)} The total of

  • 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...
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    Dissertation
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    loss. Given video v with only two classes {c, a} and another video v′ with also two classes {c, b}, we

  • Network coding for multi-user wireless networks

    Creator:
    Nguyen, Dong Van
    Abstract:
    Until a few years ago, wireless-capable laptops were considered novelties by many. It is now hard to find a laptop or a hand-held computing device that is not wireless-ready. As wireless devices are becoming commodities, they have also become an indispensable part of the modern society. Not surprisingly, research in...
    Resource Type:
    Dissertation
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    computational rates. c©Copyright by Dong Nguyen June 10, 2009 All Rights Reserved 2010 Electrical

  • 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...
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    Dissertation
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    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 B PCCA Likelihood Gradient . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 LIST OF

  • 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...
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    Dissertation
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    wrangling with robust learning algorithms. c©Copyright by Jose Manuel Picado Leiva May 28, 2019 All

  • 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...
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    Dissertation
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    .10 The density signature C.10(a) and the semi-log plot of the density signa­ ture C.10(b) for October

  • Behavior graphs for data-driven animation of 3d characters

    Creator:
    Srinivasan, Madhusudhanan
    Abstract:
    In this dissertation, we present a user-in-the-loop method for the design of an interactive motion data structure that benefits from the advantages of both motion graphs and blend-based techniques. Our novel approach automatically analyzes a traditional motion graph built from labeled motion clips. The result is a more condensed, coarser...
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    Dissertation
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    strengths and weaknesses of our approach. c©Copyright by Madhusudhanan Srinivasan February 9, 2009 All

  • From shape-based object recognition and discovery to 3D scene interpretation

    Creator:
    Payet, Nadia
    Abstract:
    This dissertation addresses a number of inter-related and fundamental problems in computer vision. Specifically, we address object discovery, recognition, segmentation, and 3D pose estimation in images, as well as 3D scene reconstruction and scene interpretation. The key ideas behind our approaches include using shape as a basic object feature, and...
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    Dissertation
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    , pairs (u, s′) and (v, v′) do not have similar layouts in image 1 and image 2. (b) Case 2: Estimating δ(u