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Filtering by: DOI 10.1090/S0002-9939-2013-11697-7 Remove constraint DOI: 10.1090/S0002-9939-2013-11697-7 Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan

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  • Incorporating labeled features into image classification using generalized expectation

    Creator:
    Moore, Travis
    Abstract:
    Image classification is a difficult problem, often requiring large training sets to get satisfactory results. However this is a task that humans perform very well, and incorporating user feedback into these learning algorithms could help reduce the dependency on large amounts of labeled training data. This process has already been...
    Resource Type:
    Masters Thesis
    Full Text:
    Master of Science in Computer Science presented on November 21, 2013. Title: Incorporating Labeled

  • Fast queuing policies via convex relaxation

    Creator:
    Nguyen-Huu, Duong
    Abstract:
    Traditionally, networking protocol designs have placed much emphasis on point-to-point reliability and efficiency. With the recent rise of mobile and multimedia applications, other considerations such as power consumption and/or Quality of Service (QoS) are becoming increasingly important factors in designing network protocols. As such, we present a new flexible framework...
    Resource Type:
    Masters Thesis
    Full Text:
    of Master of Science in Electrical and Computer Engineering presented on May 20, 2013. Title: Fast

  • Machine learning for improving the quality of citizen science data

    Creator:
    Yu, Jun
    Abstract:
    Citizen Science is a paradigm in which volunteers from the general public participate in scientific studies, often by performing data collection. This paradigm is especially useful if the scope of the study is too broad to be performed by a limited number of trained scientists. Although citizen scientists can contribute...
    Resource Type:
    Dissertation
    Full Text:
    Computer Science presented on December 3, 2013. Title: Machine Learning for Improving the Quality of

  • Adaptation-based programming

    Creator:
    Bauer, Tim
    Abstract:
    Partial programming is a field of study where users specify an outline or skeleton of a program, but leave various parts undefined. The undefined parts are then completed by an external mechanism to form a complete program. Adaptation-Based Programming (ABP) is a method of partial programming that utilizes techniques from...
    Resource Type:
    Dissertation
    Full Text:
    31, 2013. Title: Adaptation-Based Programming Abstract approved: Martin Erwig Partial

  • Revenue-based spectrum management via Markov decision process

    Creator:
    Zhu, Pingan
    Abstract:
    We consider the problem of wireless spectrum management in cognitive wireless networks that maximizes the revenue for a spectrum operator. Specifically, we study the problem on how a wireless spectrum operator can optimally allocate its limited spectrum to various classes users/devices who pay differently for their spectrum per unit time....
    Resource Type:
    Masters Thesis
    Full Text:
    Science and Mathematics presented on September 23, 2013. Title: Revenue-Based Spectrum Management Via

  • From multitarget tracking to event recognition in videos

    Creator:
    Brendel, William
    Abstract:
    This dissertation addresses two fundamental problems in computer vision—namely, multitarget tracking and event recognition in videos. These problems are challenging because uncertainty may arise from a host of sources, including motion blur, occlusions, and dynamic cluttered backgrounds. We show that these challenges can be successfully addressed by using a multiscale,...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 6.10 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125 7

  • Recognizing human group activities in video through mining optimal features

    Creator:
    Amer, Mohamed R.
    Abstract:
    Given a video, we would like to recognize group activities, localize video parts where these activities occur, and detect actors involved in them. To this and, we propose a novel, mid-level feature, called control point, for representing group activities. The control points are aimed at summarizing visual cues, lifting from...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 6.2 Extracting Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 7 Learning 37

  • 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...
    Resource Type:
    Dissertation
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 From a

  • Characterizing and Addressing Dataset Shift with Deep Learning

    Creator:
    Olson, Matthew L.
    Abstract:
    This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
    Resource Type:
    Dissertation
    Full Text:
    ”. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 The components of a pre-trained agent. . . . . . . . . . . . . . . . . . . 13 2.3 An

  • Listing as a Potential Connection between Sets of Outcomes and Counting Processes

    Creator:
    Erickson, Sarah A.
    Abstract:
    Counting problems are rich in opportunities for students to make meaningful mathematical connections and develop non-algorithmic thinking; their accessible nature and applications to computer science make counting problems a valuable part of mathematics curricula. However, students struggle in various ways with counting, and while previous studies have indicated that listing...
    Resource Type:
    Masters Thesis
    Full Text:
    strategies, and I frame my findings about their understanding using Lockwood’s (2013) model of students