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Filtering by: Creator McKinnon, P. F. Remove constraint Creator: McKinnon, P. F. Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan

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  • 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:
    item selection, with possible item rejection” (p. 460). Solution Strategy F “Complete odometer

  • Bayesian optimization with empirical constraints

    Creator:
    Azimi, Javad
    Abstract:
    Bayesian Optimization (BO) methods are often used to optimize an unknown function f(•) that is costly to evaluate. They typically work in an iterative manner. In each iteration, given a set of observation points, BO algorithms select k ≥ 1 points to be evaluated. The results of those points are...
    Resource Type:
    Dissertation
    Full Text:
    (BO) methods are often used to optimize an unknown function f(·) that is costly to evaluate. They

  • Action Selection for Heterologous Control of a Continuous-Output Myoelectric Prosthesis

    Creator:
    Sylwester, Sean T.
    Abstract:
    Significance: Movement intent decoding algorithms can interpret human bioelectrical signals to control prosthetic limbs with many degrees of freedom (DOFs). This work involves decoding volitional movement intent from surface electromyogram (sEMG) signals to control prosthetic arms. To train these algorithms, patients flex their muscles to “follow” a movement prompt, and...
    Resource Type:
    Masters Thesis
    Full Text:
    MedianRef map- ping (p = 0.0017, p = 0.0497, respectively). The Action Screening algorithm also

  • 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:
    a pruning function (P) to remove bad candidate labelings generated by the successor function. This

  • 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...
    Resource Type:
    Dissertation
    Full Text:
    . Observed nodes during training are shaded gray. When p = 0, the mixture of AR models will degenerate to a

  • Planning in multi-agent partially observable domains using sparse sampling

    Creator:
    Donneau-Golencer, Thierry D.
    Abstract:
    A large number of sequential decision-making problems in uncertain environments can be modeled as Markov Decision Processes (MDPs). In such settings, an agent can observe at each time step the state of the environment and then executes an action, causing a stochastic transition to a new state of the environment...
    Resource Type:
    Masters Thesis
    Full Text:
    ���<[#†*��+D�<> \�+M�1G<"�+-0/ -`'0�9 ?D�<p&E<"�!D9Qz8(&27�7+�!*L&%MO�!7��+�{:FD\<p&r<>�2U?�f<6�^&2D�MO�!�9/ˆD

  • 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:
    expectation regularization term introduced by Druck et al [10], is of the form −GE(P T , P̂θ) = − ∑ f∈F KL

  • 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:
    probability max y p(y|x̄) may be arbitrarily close to 1 when fθ is a nonlinear neural network [Hein et al

  • Learning MDP action models via discrete mixture trees

    Creator:
    Wynkoop, Michael S.
    Abstract:
    This thesis addresses the problem of learning dynamic Bayesian network (DBN) models to support reinforcement learning. It focuses on learning regression tree models of the conditional probability distributions of the DBNs. Existing algorithms presume that the stochasticity in the domain can be modeled as a deterministic function with additive noise....
    Resource Type:
    Masters Thesis
    Full Text:
    significant difference between DMT and the indicated algorithm (p < 0.05; paired t test). TTP DMT-F DMT-S

  • 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:
    Figure 3.5: Tangent at x0 = 0.3 of the function f(x) = (1− √ x)2 P =  r0 p0 q1 r1 p1