Hasil Pencarian - Devarani Devi Ningombam

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  1. 1
    Distance-Constrained Outage Probability Analysis for Device-to-Device Communications Underlaying Cellular Networks with Frequency Reuse Factor of 2

    Distance-Constrained Outage Probability Analysis for Device-to-Device Communications Underlaying Cellular Networks with Frequency Reuse Factor of 2 oleh Devarani Devi Ningombam, Seokjoo Shin

    Diterbitkan 2018-10-01
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  2. 2
    Traffic Offloading in Multicast Device-to-Device Cellular Networks: A Combinatorial Auction-Based Matching Algorithm

    Traffic Offloading in Multicast Device-to-Device Cellular Networks: A Combinatorial Auction-Based Matching Algorithm oleh Devarani Devi Ningombam, Seokjoo Shin

    Diterbitkan 2020-02-01
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  3. 3
    Optimal Resource Management and Binary Power Control in Network-Assisted D2D Communications for Higher Frequency Reuse Factor

    Optimal Resource Management and Binary Power Control in Network-Assisted D2D Communications for Higher Frequency Reuse Factor oleh Devarani Devi Ningombam, Seokjoo Shin

    Diterbitkan 2019-01-01
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  4. 4
    Performance analysis and comparison of various machine learning algorithms for early stroke prediction

    Performance analysis and comparison of various machine learning algorithms for early stroke prediction oleh Vinay Padimi, Venkata Sravan Telu, Devarani Devi Ningombam

    Diterbitkan 2023-12-01
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  5. 5
    CuMARL: Curiosity-Based Learning in Multiagent Reinforcement Learning

    CuMARL: Curiosity-Based Learning in Multiagent Reinforcement Learning oleh Devarani Devi Ningombam, Byunghyun Yoo, Hyun Woo Kim, Hwa Jeon Song, Sungwon Yi

    Diterbitkan 2022-01-01
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  6. 6
    QSOD: Hybrid Policy Gradient for Deep Multi-agent Reinforcement Learning

    QSOD: Hybrid Policy Gradient for Deep Multi-agent Reinforcement Learning oleh Hafiz Muhammad Raza Ur Rehman, Byung-Won On, Devarani Devi Ningombam, Sungwon Yi, Gyu Sang Choi

    Diterbitkan 2021-01-01
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  7. 7
    A Novel and Efficient Influence-Seeking Exploration in Deep Multiagent Reinforcement Learning

    A Novel and Efficient Influence-Seeking Exploration in Deep Multiagent Reinforcement Learning oleh Byunghyun Yoo, Devarani Devi Ningombam, Sungwon Yi, Hyun Woo Kim, Euisok Chung, Ran Han, Hwa Jeon Song

    Diterbitkan 2022-01-01
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