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data learning » deep learning (توسيع البحث)
يعرض 41 - 60 نتائج من 200 نتيجة بحث عن 'distributed data learning', وقت الاستعلام: 0.07s تنقيح النتائج
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    Data-Driven Detection of Electricity Theft Cyberattacks in PV Generation حسب Shaaban, Mostafa

    منشور في 2021
    "…This paper proposes a data-driven approach based on machine learning to detect such thefts. …"
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  6. 46

    RL-OPRA: Reinforcement Learning for Online and Proactive Resource Allocation of crowdsourced live videos حسب Emna Baccour (16896366)

    منشور في 2020
    "…As the optimization is not adequate for online serving, we propose a real-time approach based on Reinforcement Learning (RL), namely RL-OPRA, which adaptively learns to optimize the allocation and serving decisions by interacting with the network environment. …"
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    The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs حسب Muhammad Kashif (3923483)

    منشور في 2023
    "…<p dir="ltr">Recent advances in quantum computing and machine learning have brought about a promising intersection of these two fields, leading to the emergence of quantum machine learning (QML). …"
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    GDLL: A Scalable and Share Nothing Architecture Based Distributed Graph Neural Networks Framework حسب Duong Thi Thu Van (19499206)

    منشور في 2022
    "…<p dir="ltr">Deep learning has recently been shown to be effective in uncovering hidden patterns in non-Euclidean space, where data is represented as graphs with complex object relationships and interdependencies. …"
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    Online Transient Stability Assessment Under Concept Drift: An ARF-Method-Assisted Federated Learning for Data Streams حسب Mohamed Massaoudi (16888710)

    منشور في 2025
    "…FedARF facilitates distributed knowledge aggregation learned from various heterogeneous local data sensors (clients) to predict and evaluate the TSA status with minimal communication overhead. …"
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    Novel Evasion Attacks Against Adversarial Training Defense for Smart Grid Federated Learning حسب Atef H. Bondok (19482352)

    منشور في 2023
    "…Adversarial training (AT) has shown promise in countering evasion threats on machine learning models. This paper, first, investigates the susceptibility of traditional electricity theft classifiers trained by FL to EAs for both independent and identically distributed (IID) and Non-IID consumption data. …"