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[논문 리뷰] Federated Learning: Challenges, Methods, and Future Directions

논문 링크: Federated Learning: Challenges, Methods, and Future DirectionsFederated learning involves training statistical models over remote devices or siloed data centers, such as mobile phones or hospitals, while keeping data localized. Training in heterogeneous and potentially massive networks introduces novel challenges thaieeexplore.ieee.org 출처: T. Li, A. K. Sahu, A. Talwalkar and V. Smith, "F..

Artificial Intelligence 2025.12.23
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    • Wireless Communications (44)
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beyond 6G, AI-native, semantic communication, 6g, spectral efficiency, Channel estimation, contextual reasoning, Ai, Intelligent wireless networks, time-division duplexing (TDD), Federated Learning, energy efficiency, Semantic communications, massive MIMO systems, Joint source-channel coding, semantic learning, ML, orthogonal frequency division multiplexing (OFDM), Large Language Model, pilotcontamination,

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