This dataset accompanies the manuscript "Telemetry-aware federated learning on heterogeneous edge devices: an experimental study". The dataset contains telemetry measurements collected from a federated learning testbed consisting of a Raspberry Pi 5 and an NVIDIA Jetson Nano running the Flower federated learning framew...
Manikandaprabu Nallasivam· Zenodo (CERN European Organi...· 0 citations
Federated learning (FL) offers a promising approach to distributed machine learning, enabling model training on decentralized devices without directly exchanging sensitive data. However, the inherent vulnerability of FL systems to Byzantine failures – where malicious participants intentionally corrupt the learning proc...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
This dataset accompanies the manuscript "Telemetry-aware federated learning on heterogeneous edge devices: an experimental study". The dataset contains telemetry measurements collected from a federated learning testbed consisting of a Raspberry Pi 5 and an NVIDIA Jetson Nano running the Flower federated learning framew...
Manikandaprabu Nallasivam· Zenodo (CERN European Organi...· 0 citations
This package contains the code and generated data behind the quantitative results of the survey "Flows and Rounds: A Survey of Distributed Neurodynamic Optimization and Federated Learning", submitted to Neurocomputing. It reproduces every number, table, and figure in Sections 2.3 and 8 of the article. No third-party, p...
Tien Hung Giang· Mendeley Data· 0 citations
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Federated learning (FL) offers a promising approach to distributed machine learning, enabling model training on decentralized devices without directly exchanging sensitive data. However, the inherent vulnerability of FL systems to Byzantine failures – where malicious participants intentionally corrupt the learning proc...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
The results indicate that the DFL system achieves accuracy comparable to centralized baselines in most scenarios, and that a cross-node validation mechanism reliably excludes poisoned updates as long as fewer than half of the nodes are compromised, clarify both the promise and the current limitations of decentralized,...
Tiago Ferreira, João Durães· Journal of Sensor and Actuat...· 0 citations
Adolescent idiopathic scoliosis (AIS) is the most common three-dimensional spinal deformity among adolescents, characterized by a coronal curvature of > 10°, often accompanied by vertebral rotation and abnormal sagittal alignment, which can lead to severe cardiopulmonary and neurological dysfunction. For moderate-to-se...
Yawei Zhang, Jingyu Liu, Zijie An et al.· Artificial Intelligence Surg...· 0 citations
Artificial intelligence (AI) is transforming photovoltaic (PV) systems from passive generators into self-forecasting, self-diagnosing, and self-optimizing energy assets. This review synthesizes 170 Scopus-indexed documents published between 2020 and 2026 across six technical domains: solar resource and PV power forecas...
R. Senthil, R. Priya, S. Radhakrishnan et al.· Solar· 0 citations
Federated Learning (FL) has emerged as a promising solution for data hunger in centralized learning. This paradigm enables privacy with multiple clients to train a shared-task model collaboratively without exposing their local data. While being a key component in any learning system, data is also a primary source of vu...
Federated Learning (FL) has emerged as a promising paradigm owing to its significant advantages over conventional centralized machine learning approaches. It is a decentralized learning framework in which a global model is iteratively constructed by aggregating locally trained models from distributed clients, thereby e...
Kasun Eranda Wijethilake, Adnan Mahmood, Fahmida Islam et al.· Computer Networks· 0 citations
Federated learning (FL) has emerged as a secure paradigm for collaborative training among clients. Without data centralization, FL allows clients to share local information in a privacy-preserving manner. This approach has gained considerable attention, promoting numerous surveys to summarize the related works. However...
Jiawei Shao, Zijian Li, Wenqiang Sun et al.· ACM Computing Surveys· 12 citations
It is discussed how FL can enable scalable, privacy-preserving AI models, and future directions for standardizing and validating FL-based approaches in clinical workflows are outlined.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 7, 2026
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
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