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Filtering by: Creator Chang, Xiao Lan Remove constraint Creator: Chang, Xiao Lan Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Graph Imitation Learning for Optimal Joint Beamforming and Antenna Selection

    Creator:
    Shrestha, Sagar
    Abstract:
    Transmit beamforming is an important technique employed to improve efficiency and signal quality in wireless communication systems by steering signals towards their in- tended users. It often arises jointly with the antenna selection problem due to various reasons, such as limited number of radio frequency (RF) chains and energy/resource effi-...
    Resource Type:
    Masters Thesis
    Full Text:
    Imitation Learning For Optimal Joint Beamforming and Antenna Selection Abstract approved: Xiao Fu

  • HiNoVa: A Novel Open-Set Detection Method for Automating RF Device Authentication

    Creator:
    Puppo, Luke
    Abstract:
    New capabilities in wireless network security are now possible through deep learning, which can identify and leverage patterns in radio frequency (RF) data. One area of deep learning, known as open set detection, is focused on detecting data instances from new devices encountered during deployment that were not previously seen...
    Resource Type:
    Masters Thesis

  • Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

    Creator:
    Khorram, Saeed
    Abstract:
    In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...
    Resource Type:
    Masters Thesis
    Full Text:
    Oregon State University. Futher, I would like to thank Zhongang Qi and Xiao Fu for the joint discussions

  • Multiple Instance Learning for Histopathological Image Classification

    Creator:
    Lai, Phung
    Abstract:
    In histopathological image analysis, image classification as well as pattern detection play a crucial role in the diagnosis and treatment process since the goal is to not only differentiate cancer types but also identify cancerous manifestations. Fully supervised learning strategies tend to address these problems using manually annotated cancerous regions...
    Resource Type:
    Capstone Project
    Full Text:
    . Xiao Fu, and Dr. Molly Megraw for their attendance and advice in my defense. I would also like to

  • Crop Rotation Economic and Environmental Impact Decision Aid (CREEDA) : a COM-based application

    Creator:
    Chang, Song
    Abstract:
    CREEDA (Crop Rotation Economic and Environmental Impact Decision Aid) is a Windows application for assessing economic and environmental impacts of agricultural activities. In implementing it, we extended the ProCosts database and incorporated the RUSLE (Revised Universal Soil-Loss Equation) application and the SCI (Soil Conditioning Index) application as COM components. ProCosts,...
    Resource Type:
    Capstone Project
    Full Text:
    University Song Chang In partial fulfillment of the requirement of The requirements for Degree of

  • Database transaction traffic algorithms

    Creator:
    Chang, Chung Wen
    Resource Type:
    Capstone Project
    Full Text:
    Wen Chang · A Research Project Report submitted to Department of Computer Science Oregon State

  • Scheduling and Online Planning in Stochastic Diffusion Networks

    Creator:
    Xue, Shan
    Abstract:
    Diffusion processes in networks are common models for many domains, including species colonization, information/idea cascade, disease propagation and fire spreading. In diffusion networks, a diffusion event occurs when a behavior spreads from one node to the other following a probabilistic model, where the behavior could be species, an idea, a...
    Resource Type:
    Dissertation
    Full Text:
    professors in my Ph.D. committee: Prof. Tom Di- etterich, Prasad Tadepalli, Lan Xue, and Gary Egbert. I

  • Partitioning-Guided K-Means for Effective Empty Cluster Resolution in Extreme Model Compression

    Creator:
    Huang, Tianhong
    Abstract:
    Compactness in deep learning can be critical to a model’s viability in low-resource applications, and a common approach to extreme model compression is quantization. We consider Iterative Product Quantization (iPQ) with Quant-Noise [Fan et al., 2020] to be state-of-the-art in this area, but this quantization framework suffers from preventable inference...
    Resource Type:
    Masters Thesis
    Full Text:
    applications or so reduced in size as to limit their general performance and wide-spread applicability [Lan et

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation
    Full Text:
    speech, but they are discarded in the speech recognition step. (d) There exist many non-orthographic lan

  • Developing true diagnostic software

    Creator:
    Prusynski, Michael
    Abstract:
    This document describes the need for, and design of, diagnostic software that provides circuit verification, fault isolation, and troubleshooting aids. The difference between verification software and true diagnostic software is explained. A modular design of diagnostic software is proposed, consisting of a series of 3-part tests, a test manager, results...
    Resource Type:
    Capstone Project
    Full Text:
    -Kernel fl-Bus tests f2-Interrupts f3-LAN circuitry - 21 - • Run all tests, PrintErrors, NoLoop