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Filtering by: Creator Fu-Mei Chen Remove constraint Creator: Fu-Mei Chen Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science

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  • Applying Deep Learning in Street View Imagery for Environmental Health Research

    Creator:
    Zhang, Yifang
    Abstract:
    Urban green space is associated with multiple physical and mental health outcomes. Several benefits of green space, such as stress reduction and attention restoration, are dependent on visual perception of green space exposures. However, traditional green space exposure measures do not capture street-level exposures. In this project, we apply deep...
    Resource Type:
    Capstone Project
    Full Text:
    : ______________________________________________________ Dr. Lizhong Chen Urban green space is associated with multiple physical and mental

  • Machine Learning for Architectural Design Space Exploration and Resource Control

    Creator:
    Penney, Drew D.
    Abstract:
    Machine learning has enabled significant advancements in diverse fields, yet, with a few exceptions, has had limited impact on computer architecture. Recent work, however, has begun to explore broader application to design, optimization, and simulation. Notably, machine-learning-based strategies often surpass prior state-of-the-art analytical, heuristic, and human-expert approaches. This thesis first...
    Resource Type:
    Masters Thesis
    Full Text:
    Learning for Architectural Design Space Exploration and Resource Control Abstract approved: Lizhong Chen

  • Machine learning for computer architecture design and optimization

    Creator:
    Penney, Drew
    Abstract:
    Machine learning applied to computer architecture has rapidly transitioned from a theoretical novelty to being a driving force behind design, control, and simulation in practically all components. These machine-learning-based methodologies are further notable for their scalability to increasingly complex design challenges, which has allowed these methodologies to surpass the prior...
    Resource Type:
    Dissertation
    Full Text:
    Chen Machine learning applied to computer architecture has rapidly transitioned from a theoretical

  • Predicting and Improving Throughput, Responsiveness and Battery Life of Computer Systems by Machine Learning

    Creator:
    Li, Yunfan
    Abstract:
    The Machine Learning (ML) algorithms are increasingly explored in varies of fields including designing and optimizing computer systems. Recent research, such as optimizing memory/cache prefetching by ML training or predicting traffic pattern in throughput processors, also exhibits a promising future of introducing ML into computer system design and optimization. Throughput...
    Resource Type:
    Dissertation
    Full Text:
    approved: Lizhong Chen The Machine Learning (ML) algorithms are increasingly explored in varies of

  • Towards Deep Learning Model Portability for Domain-Agnostic Device Fingerprinting

    Creator:
    Gaskin, Jared
    Abstract:
    In recent years, RF (Radio Frequency) device fingerprinting using deep learning has emerged as a method of identifying devices solely by their RF transmissions. Conventional approaches to this type of device fingerprinting are not portable to different domains. That is, if a model for this purpose is trained on data...
    Resource Type:
    Masters Thesis
    Full Text:
    : Bechir Hamdaoui Lizhong Chen In recent years, RF (Radio Frequency) device fingerprinting using deep

  • Routerless Network-on-chip

    Creator:
    Alazemi, Fawaz
    Abstract:
    Traditional bus-based interconnects are simple and easy to implement, but the scalability is greatly limited. While router-based networks-on-chip (NoCs) offer superior scalability, they also incur significant power and area overhead due to complex router structures. In this thesis, a new class of on-chip networks, referred to as Routerless (RL) NoCs,...
    Resource Type:
    Dissertation
    Full Text:
    : Routerless Network-on-chip Abstract approved: Bella Bose Lizhong Chen Traditional bus-based interconnects

  • 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

  • Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms

    Creator:
    Ibrahim, Shahana
    Abstract:
    Crowdsourcing is a popular paradigm to address the high demands for labeled data in big data deluge. It aims to produce accurate labels by effectively integrating noisy, non-expert labeling from crowdsourced workers (annotators). The machine learning community has been studying effective crowdsourcing methods for many years, and many models and...
    Resource Type:
    Masters Thesis
    Full Text:
    : Crowdsourcing via Pairwise Co-occurrences: Identifiability and Algorithms Abstract approved: Xiao Fu

  • Large Scale Tensor Decomposition Algorithms Using Block-randomized Stochastic Proximal Gradient

    Creator:
    Gao, Cheng
    Abstract:
    We consider the problem of computing the cannonical polyadic decomposition (CPD) for large-scale dense tensors. This work is a combination of alternating least squares and fiber sampling. Data sparsity can be leveraged to handle large tensor CPD, but this route is not feasible for dense data. Inspired by stochastic optimization's...
    Resource Type:
    Masters Thesis
    Full Text:
    : Xiao Fu We consider the problem of computing the cannonical polyadic decomposition (CPD) for large

  • Object Tracking-by-Segmentation in Videos

    Creator:
    Chen, Sheng
    Abstract:
    This thesis focuses on the problem of object tracking. Given a video, the general objective of tracking is to track the location over time of one or more targets in the image sequence. This is a very challenging task as algorithms need to deal with problems such as appearance variations,...
    Resource Type:
    Dissertation
    Full Text:
    thesis.dvi AN ABSTRACT OF THE THESIS OF Sheng Chen for the