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Filtering by: Creator Jolles, Anna E. Remove constraint Creator: Jolles, Anna E. Degree Field Computer Science Remove constraint Degree Field: Computer Science Degree Level Master's Remove constraint Degree Level: Master's

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  • Maximum flow in planar digraphs

    Creator:
    Harutyunyan, Anna
    Abstract:
    Worst-case analysis is often meaningless in practice. Some problems never reach the anticipated worst-case complexity. Other solutions get bogged down with impractical constants during implementation, despite having favorable asymptotic running times. In this thesis, we investigate these contrasts in the context of finding maximum flows in planar digraphs. We suggest...
    Resource Type:
    Masters Thesis
    Full Text:
    THESIS OF Anna Harutyunyan for the degree of Master of Science in Computer Science presented on

  • A two level minimal perfect hash function for large data sets

    Creator:
    Barrar, Howard
    Abstract:
    Recently several minimal perfect hashing functions far small static word sets have been developed. However, they are limited to sets of 50 words or less. In this paper, a Two Level Minimal Perfect Hash Function for large data sets is given. It partitions a large static set into small sets...
    Resource Type:
    Capstone Project
    Full Text:
    :e:.._,-A.,_ b_eA_· __ /-1-J-

  • Counterfactual States for Atari Agents via Generative Deep Learning

    Creator:
    Olson, Matthew L.
    Abstract:
    Although deep reinforcement learning agents have produced impressive results in many domains, their decision making is difficult to explain to humans. To address this problem, past work has mainly focused on explaining why an action was chosen in a given state. A different type of explanation that is useful is...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2 The encoder E, generator G, and discriminator D learn a model of the external environment for

  • End-user assertions : propagating their implications

    Creator:
    Summet, Jay W.
    Abstract:
    Spreadsheet languages are the most commonly used end-user programming paradigm, yet spreadsheets commonly contain errors. Research shows that a significant number of spreadsheets (20%-40%) created by end users contain errors. In an attempt to reduce this error rate, this work presents an assertion propagation system for an end-user spreadsheet programming...
    Resource Type:
    Masters Thesis
    Full Text:
    from the high-level specification language Anna [Luckham 1985; Sankar 1991; Rosenblum et al. 1986

  • Evaluation of collaborative filtering and content based filtering recommenders in jTutors (an online intelligent tutoring system)

    Creator:
    Appasamy, Bharatwaj
    Abstract:
    Software engineers often need help with discovering and learning how to use APIs. For example, software engineers who are starting to learn Java, and they want to implement a certain feature in a program, they might want to reuse existing APIs in order to save time versus rewriting it themselves...
    Resource Type:
    Masters Thesis
    Full Text:
    ................................................................. 8 2.3 Recommenders in the context of E-Learning Systems ..................................... 9

  • A Study of Temporal Convolutional Neural Networks for Music Language Modeling as Applied to Automatic Music Transcription

    Creator:
    Meyn, Matthew
    Abstract:
    Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
    Resource Type:
    Capstone Project
    Full Text:
    logistic sigmoid function, p̂ = 1 1+e−z , and interpreted as the probability P (yij = 1) of pitch i being

  • Engineering Student Perspectives of a New Required Programming Course

    Creator:
    Garcia Ramirez, Jessica
    Abstract:
    We present student perceptions of a new first-year engineering programming class that was designed by informed research practices. While the College of Engineering at Oregon State University saw a lot of major switching in the first year, there were not many students switching into computer science (CS). This could have...
    Resource Type:
    Masters Thesis
    Full Text:
    experience, knowledge organization, self- e�cacy, and class size were factors impacting student performance

  • Local and Global Explanations for Deep Image Classification via Structured Attention Graphs

    Creator:
    Shitole, Vivswan
    Abstract:
    Attention maps are popular tools of explaining the decisions of convolutional neural net-works (CNNs) for image classification. Typically, for each image of interest, a single attention map is produced, which assigns weights to pixels based on their importance to the classification. We argue that a single attention map provides an...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . 69 E Cluster Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 LIST

  • Exploration of regression models for cancer noncoding mutation recurrence

    Creator:
    Xu, Tanjin
    Abstract:
    An important impact of the genome technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Integrated with current well-studied massive knowledge and findings about the role of protein-coding mutations in cancer, demystifying the functional...
    Resource Type:
    Masters Thesis
    Full Text:
    ) = e−λiλyii yi! , λi > 0, yi ∈ {0, 1, 2, . . . }. (2.4) The most common formulation for λi is the log

  • Deep Segmentation in Plant Phenomics

    Creator:
    Kaur, Damanpreet
    Abstract:
    The abilities of plant biologists to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation and mainly to collect this data on a high-throughput scale at low cost. Deep learning-based methods have demonstrated unprecedented potential to automate...
    Resource Type:
    Masters Thesis