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Filtering by: Creator Hoffman, Justine D. Remove constraint Creator: Hoffman, Justine D. Academic Affiliation Electrical Engineering and Computer Science Remove constraint Academic Affiliation: Electrical Engineering and Computer Science Decade 2020-2029 Remove constraint Decade: 2020-2029

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  • 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:
    dividing line (in 2-D) or hyperplane (in high dimensions) between examples, then uses examples along this

  • AQ-CAR : adaptive-queueing congestion-aware routing for datacenter traffic forwarding

    Creator:
    Alanazi, Sultan and Hamdaoui, Bechir
    Abstract:
    Modern datacenters are constructed with multirooted tree topologies and support multiple service queues per switch port. They support a wide variety of applications and services with stringent performance needs and conflicting requirements. To meet these requirements, recent works focus on load balancing or ECN marking approaches. Though existing load-balancing approaches...
    Resource Type:
    Technical Report
    Full Text:
    ) Medium (d) Large Fig. 4: FCT statistics across different flow sizes for Mix workload (a) Overall (b

  • Fair packet enqueueing and marking in multi-queue datacenter networks

    Creator:
    Alanazi, Sultan and Hamdaoui, Bechir
    Abstract:
    Recently, Explicit Congestion Notification (ECN) has been leveraged by most Datacenter Network (DCN) protocols for congestion control to achieve high throughput and low latency. However, the majority of these approaches assume that each switch port has one queue while current industry trends towards having multiple queues per switch port. To...
    Resource Type:
    Technical Report
    Full Text:
    mining (d) WRR:Hadoop (e) WRR:Cache (f) DWRR:Mix (g) DWRR:Web search (h) DWRR:Data mining (i

  • Inclusive Software Design and Its Methods for Beyond-WIMP User Interfaces

    Creator:
    Fallatah, Abrar
    Abstract:
    While digital inclusivity researchers and software practitioners have been trying to address exclusion biases in Windows, Icons, Menus, and Pointers (WIMP) user interfaces (UIs) for a long time, little has been done to investigate if and how inclusive software design and its methods that have been devised for WIMP UIs...
    Resource Type:
    Dissertation
    Full Text:
    ), Semi-Open (c,d), and Self-Contained (e,f). The locations of the ethnographer/observer, wizard and the

  • The InclusiveMag Method: A Start Towards More Inclusive Software for Diverse Populations

    Creator:
    Mendez, Christopher
    Abstract:
    How can software practitioners assess whether their software supports diverse users? Although there are empirical processes that can be used to find “inclusivity bugs” piecemeal, what is often needed is a systematic inspection method to assess software’s support for diverse populations. To help fill this gap, this thesis introduces InclusiveMag,...
    Resource Type:
    Masters Thesis

  • Individual Fairness Optimization in Machine Learning with Minimax Loss and an Abstain Option

    Creator:
    Behnoudfar, Ali
    Abstract:
    In this thesis, a new learning algorithm is introduced that is targeted towards individual fairness. In order to be individually fair, mispredictions need to be avoided as each such prediction means the learning algorithm was unfair towards some individual. Therefore, achieving individual fairness implies having a perfect classifier, which is...
    Resource Type:
    Masters Thesis
    Full Text:
    corresponding to whether the sensitive feature is observed or not. Given the similarity measure d(x1, x2), SenSR

  • Error Analysis of Object Detection Models with Interactive User Interfaces

    Creator:
    Oh, Dayeon
    Abstract:
    Object detection models are being widely used in many applications, such as autonomous driving, construction management, and cancer detection. Evaluating the performance of the object detection model is more complicated than other computer vision models such as image classification models. Most of the images have several objects to be detected,...
    Resource Type:
    Capstone Project
    Full Text:
    Bibliography [1] Boyla D., Foley S., Hays J., Hoffman J.: TIDE: A General Toolbox for Identifying Object

  • Uncertainty in Deep Learning with Implicit Neural Networks

    Creator:
    Ratzlaff, Neale
    Abstract:
    The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
    Resource Type:
    Dissertation
    Full Text:
    Diversity . . . . . . . . . . . . . . . . 33 4.3.3 1-D Regression

  • CMOS Transducers and Programmable Interface Circuits for Resource-Efficient Sensing Applications

    Creator:
    Sengupta, Shaan
    Abstract:
    Modern sensors are complex systems comprising multiple sub-systems such as transducers, analog and mixed-signal interface circuits, digital processing circuits, and packaging. Over the last few decades, innovations in these sub-systems combined with their increased integration in complementary metal-oxide semiconductor (CMOS) processes have led to the rapid growth in sensors for...
    Resource Type:
    Dissertation
    Full Text:
    ]. . . . . . . . . . . . . . . . 20 2.8 3-D illustration of the structure of the on-chip resistive sensing element formed in the top

  • A case for application-based linear transformers : applied towards text-to-spectrogram

    Creator:
    Agostinelli, Victor
    Abstract:
    Various natural language processing (NLP) tasks necessitate deep models that are fast, efficient, and small based on their ultimate application at the edge or elsewhere. While significant investigation has furthered the efficiency and reduced the size of these models, reducing their downstream latency without significant trade-offs remains a difficult task....
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 D Synthetic Dataset for Brief Latency Comparisons . . . . . . . . . . . 80 --- LIST OF