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Filtering by: Creator Obermeyer, Angela L. Remove constraint Creator: Obermeyer, Angela L. 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:
    ,M,L) = (8, 4, 4). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 LIST OF TABLES

  • 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:
    L•vel Algorithm Step 1 of the algorithm partitions the large data set int o s ma 11 er s et s

  • Improving User Mental Models of XAI Systems with Inclusive Design Approaches

    Creator:
    Hamid, Md Montaser
    Abstract:
    Explainable Artificial Intelligence (XAI) systems aim to improve users’ understanding of AI but rarely consider the inclusivity aspects of XAI. Without inclusive approaches, improving explanations might not work well for everyone. This study investigates leveraging users’ diverse problem-solving styles as an inclusive strategy to fix an XAI prototype, with the...
    Resource Type:
    Masters Thesis
    Full Text:
    together. Without equity, there can be neither progress nor prosperity.” [6] —Angela Glover Blackwell

  • Deep Convolutional Network on Point Clouds for 3D Scene Understanding

    Creator:
    Wu, Wenxuan
    Abstract:
    As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
    Resource Type:
    Dissertation
    Full Text:
    level l is concatenated with the upsampled feature from level l+ 1, which contains feature with a

  • Web-based Deep Segmentation of Building Structure

    Creator:
    Chen, Zehuan
    Abstract:
    Deep learning and neural network has been widely used in research, deep learning has empowered many tasks such as point clouds segmentation and shape recognition. One of the main advantages of deep interaction point cloud segmentation is that it allows the feature extraction can be learned through neural network based...
    Resource Type:
    Masters Thesis
    Full Text:
    conversion from grayscale is to use the lightness L∗. in general, similar principles apply for this question

  • Auxiliary Tasks for Efficient Learning of Point-Goal Navigation

    Creator:
    Desai, Saurabh Satish
    Abstract:
    Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps – learning neural agents that map directly from visual observations to actions. In this work, we question whether these extreme training durations are...
    Resource Type:
    Masters Thesis
    Full Text:
    70 Number of training steps taken (experience) in million 0.2 0.4 0.6 0.8 1.0 SP L Performance

  • Computational Elucidation of the Regulatory SNPs in the Non-Coding Regions of the Human Genome

    Creator:
    Yao, Yao
    Abstract:
    We describe a series of novel computational models, CERENKOV (Computational Elucidation of the REgulatory NonKOding Variome) and its successors CERENKOV2, CERENKOV3, and Convolutional CERENKOV3, for discriminating regulatory single nucleotide polymorphisms (rSNPs) from non-regulatory SNPs within non-coding genetic loci. The CERENKOV models are designed for recognizing rSNPs in the context of...
    Resource Type:
    Dissertation
    Full Text:
    define, for the sets L ⊂ Z+ of numbered loci, S ⊂ Z+ of numbered SNPs, and R ⊂ S of numbered rSNPs. Then

  • Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

    Creator:
    Aziere, Nicolas
    Abstract:
    This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
    Resource Type:
    Dissertation
    Full Text:
    (s) Ni of size L × d, such that L ≪ |N (s)i |, by using a single layer MLP with parameters W p. With

  • Seed-Lab : a database management system for seed laboratories

    Creator:
    Maristany, Alberto G.
    Abstract:
    Seed-Lab, is a software system for managing seed laboratory information. It was developed at the Oregon State University Seed Testing Laboratory. Seed-Lab was built around a database development package Revelation, which provides its own programming language. Seed-Lab shields the user from the complexities of database management by supporting menu driven...
    Resource Type:
    Capstone Project
    Full Text:
    - ) .L..l. SOFTWARE: When this project was begun in March of 1984, networking microcomputers was still

  • Leveraging Structures of the Data in Deep Learning

    Creator:
    Li, Xingyi
    Abstract:
    The performance of deep learning frameworks could be significantly improved through considering the particular underlying structures for each dataset. In this thesis, I summarize our three work about boosting the performance of deep learning models through leveraging structures of the data. In the first work, we theoretically justify that, for...
    Resource Type:
    Dissertation
    Full Text:
    that σ : R 7→ [−1, 1] has Lipschitz constant L and satisfies σ(0) = 0. Define the class computed by a