Federated learning for wireless communications: Motivation, opportunities, and challenges
There is a growing interest in the wireless communications community to complement the
traditional model-driven design approaches with data-driven machine learning (ML)-based …
traditional model-driven design approaches with data-driven machine learning (ML)-based …
[引用][C] Federated Learning for Wireless Communications: Motivation, Opportunities, and Challenges
S Niknam, HS Dhillon, JH Reed - IEEE Communications Magazine, 2020 - cir.nii.ac.jp
Federated Learning for Wireless Communications: Motivation, Opportunities, and Challenges
| CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォーム …
| CiNii Research CiNii 国立情報学研究所 学術情報ナビゲータ[サイニィ] 詳細へ移動 検索フォーム …
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
S Niknam, HS Dhillon, JH Reed - arXiv e-prints, 2019 - ui.adsabs.harvard.edu
There is a growing interest in the wireless communications community to complement the
traditional model-based design approaches with data-driven machine learning (ML)-based …
traditional model-based design approaches with data-driven machine learning (ML)-based …
[PDF][PDF] Federated Learning for Wireless Communications: Motivation, Opportunities, and Challenges
S Niknam, HS Dhillon, JH Reed - IEEE Communications Magazine, 2020 - par.nsf.gov
There is a growing interest in the wireless communications community to complement the
traditional model-driven design approaches with data-driven machine learning (ML)-based …
traditional model-driven design approaches with data-driven machine learning (ML)-based …
[PDF][PDF] Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
S Niknam, HS Dhillon, JH Reed - arXiv preprint arXiv:1908.06847, 2019 - researchgate.net
There is a growing interest in the wireless communications community to complement the
traditional model-driven design approaches with data-driven machine learning (ML)-based …
traditional model-driven design approaches with data-driven machine learning (ML)-based …
[PDF][PDF] Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
S Niknam, HS Dhillon, JH Reed - arXiv preprint arXiv:1908.06847, 2019 - academia.edu
There is a growing interest in the wireless communications community to complement the
traditional model-driven design approaches with data-driven machine learning (ML)-based …
traditional model-driven design approaches with data-driven machine learning (ML)-based …
Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
S Niknam, HS Dhillon, JH Reed - arXiv preprint arXiv:1908.06847, 2019 - arxiv.org
There is a growing interest in the wireless communications community to complement the
traditional model-based design approaches with data-driven machine learning (ML)-based …
traditional model-based design approaches with data-driven machine learning (ML)-based …
[PDF][PDF] Federated Learning for Wireless Communications: Motivation, Opportunities and Challenges
S Niknam, HS Dhillon, JH Reed - researchgate.net
There is a growing interest in the wireless communications community to complement the
traditional model-driven design approaches with data-driven machine learning (ML)-based …
traditional model-driven design approaches with data-driven machine learning (ML)-based …