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Filtering by: Creator Hong, Wei-Li Remove constraint Creator: Hong, Wei-Li Degree Field Computer Science Remove constraint Degree Field: Computer Science

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  • Poisoning machine learning models to increase membership inference risks

    Creator:
    Le, Hoang
    Abstract:
    Deep learning is now being utilized widely in applications where sensitive data is being used for model training, for example, in health care. In this scenario, any data leakage will cause privacy concerns to whose data records are used to train the model. An attacker can actively cause privacy leakage...
    Resource Type:
    Masters Thesis
    Full Text:
    Models to Increase Membership Inference Risks Abstract approved: Sanghyun Hong Deep learning is now

  • 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...
    Resource Type:
    Dissertation
    Full Text:
    AN ABSTRACT OF THE DISSERTATION OF Juneki Hong for the

  • GraphLab : adding graphical functionality to OSU

    Creator:
    Lim, Mu-Hong
    Abstract:
    Oregon SpeedCode Universe (OSU) is a rapid prototyping system which automates the production of applications from a description of the user interface. GraphLab is a domain-specific tool which deals with several major problems concerning OSU: (1) limited functionality, that is, lacking graphical capabilities in generated applications, (2) indirect approach to...
    Resource Type:
    Capstone Project
    Full Text:
    Functionalit y to OSU Mu-Hong Lim Dr . Ted G. Lewis Department of Computer Science Oregon State

  • WebWEPP version 2.0 : Web-based water erosion prediction project

    Creator:
    Gyu Han, Hong
    Abstract:
    The WEPP (Water Erosion Prediction Project) application computes soil loss and sediment yield from a field based on the data on crops, management practices, and operations. In order to make WEPP, which is a Windows-based application, easily accessible, Web WEPP (Web-based WEPP) was developed by our research group. Web WEPP...
    Resource Type:
    Capstone Project
    Full Text:
    Project By Hong GyuHan Major Professor: Committee Member: Committee Member: Dr. Toshimi

  • 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:
    following article: Sagar Shrestha, Xiao Fu, and Mingyi Hong, “Optimal Solutions for Joint Beamforming and

  • Atomic Bifurcations of Degenerate Curves in 3D Linear Symmetric Tensor Fields

    Creator:
    Hongyu, Nie
    Abstract:
    Tensor field topology is of importance to research areas of medicine, science, and engineering. Degenerate curves are one of the crucial topological features that provide valuable insights for tensor field visualization. In this thesis, we study the atomic bifurcations of degenerate curves in 3D linear second-order symmetric tensor fields, and...
    Resource Type:
    Masters Thesis

  • Modeling Human Learning of Data Quality Rules

    Creator:
    Habibelahian, Omeed A.
    Abstract:
    The process of cleaning data is quite laborious and can be complicated by the presence of inconsistencies and other issues in the data, leading many data scientists to utilize interactive data cleaning software. However, many current state-of-the-art cleaning solutions fail to account for the reality that the human needs to...
    Resource Type:
    Masters Thesis
    Full Text:
    report. Dr. Minsuk Kahng, Dr. Weng-Keen Wong, and Dr. Si Hong Park contributed

  • Assessing and Finding Faults in AI: Two Empirical Studies

    Creator:
    Khanna, Roli
    Abstract:
    With the advent of Artificial Intelligence (AI) in every sphere of life in today's day and age, it has become increasingly important for non-AI experts to be able to comprehend the underlying logic of how AI systems work, assess them and find faults in these systems, particularly when they are...
    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:
    Abstract approved: Fuxin Li In this thesis, we introduce a novel Explanation Neural Network (XNN) to

  • 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
    Full Text:
    Plant Phenomics Abstract approved: Fuxin Li The abilities of plant biologists to characterize the