federated learning

2,169 papers

#federated learning Open access Oct 2026

FedEnD: Communication-efficient Federated Learning for non-IID data via decentralized ensemble distillation

Enrique Tomás Martínez Beltrán, Philip Giryes, Gérôme Bovet et al. · Future generations computer... · 0 citations

#federated learning Open access Nov 2026

Modelling federated learning workflows for the cloud-to-edge continuum

Wilson Valdez Solis, J. Parra-Ullauri, Dimitra Simeonidou et al. · Simulation modelling practic... · 1 citation

#federated learning Nov 2026

LCSNet–FedPerGC: An efficient federated learning framework for rice leaf disease classification in the Mekong Delta

Tieu Phung Nguyen, T. P. Dang, Minh-Khoa Tran-Thi · Computers and Electronics in... · 1 citation

#federated learning Nov 2026

Privacy-preserving occupancy prediction in multi-zone buildings based on adaptive personalized federated learning

Zhoupeng Wang, Yilin Wang, Wenli Liu et al. · Advanced Engineering Informa... · 0 citations

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#federated learning Nov 2026

IDFed: A privacy-preserving collaborative intrusion detection framework based on blockchain and federated learning

Qi Zhou, Xuechun Mao, Ying Chen · Information Sciences · 0 citations

#federated learning Nov 2026

PRISM-FedSeg: enhancing medical image segmentation through self-supervised federated learning with privacy preservation

Abdul Raheem, Zhen Yang, Malik Abdul Manan et al. · Biomedical Signal Processing... · 0 citations

#graph neural networks Sep 2026

Graph Neural Networks for Diffusion and Aggregation in Wireless Federated Learning

User devices (UDs) with non-independent and identically distributed (non-IID) data will worsen accuracy performance of the global model in federated learning (FL). Therefore, the implementation of diffusion strategies in machine learning (ML) models can enhance the effectiveness of federated learning with non-IID data....

Yunli Ji, Jiechun Zheng, Hongyang Du et al. · IEEE Transactions on Mobile... · 0 citations

#reinforcement learning Nov 2026

Stability-aware multi-objective federated learning via deep reinforcement learning: Client selection and resource optimization in dynamic edge networks

Han-Shuo Zhang, Meihua Li, Shao-Peng Guan · Ad hoc networks · 0 citations

#reinforcement learning Nov 2026

Anomaly detection method for satellite networks based on adaptive federated learning driven by deep reinforcement learning

Hui Chen, Kun Zhang, Yang Chen et al. · Information Sciences · 0 citations

From tech blogs

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Microsoft Research Blog · microsoft.com Nov 3, 2026

Learn the rules: The hacker mindset

Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.

Google DeepMind Blog · deepmind.google Nov 3, 2026

federated learning

FedEnD: Communication-efficient Federated Learning for non-IID data via decentralized ensemble distillation

Modelling federated learning workflows for the cloud-to-edge continuum

LCSNet–FedPerGC: An efficient federated learning framework for rice leaf disease classification in the Mekong Delta

Privacy-preserving occupancy prediction in multi-zone buildings based on adaptive personalized federated learning

IDFed: A privacy-preserving collaborative intrusion detection framework based on blockchain and federated learning

PRISM-FedSeg: enhancing medical image segmentation through self-supervised federated learning with privacy preservation

Graph Neural Networks for Diffusion and Aggregation in Wireless Federated Learning

Stability-aware multi-objective federated learning via deep reinforcement learning: Client selection and resource optimization in dynamic edge networks

Anomaly detection method for satellite networks based on adaptive federated learning driven by deep reinforcement learning

From tech blogs

Learn the rules: The hacker mindset

Agentic cheminformatics with Google Antigravity

Learner collaborates with MIT peers to develop book of AI insights

The sleep framework: A new way for LLMs to retain knowledge in continual learning

Q&A: How AI came to model the “messy” human mind

NVIDIA Kumo Relational Outperforms Supervised Machine Learning on Relational Data, No Training Required