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

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