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federated learning

1,721 papers

#federated learning Review Open access Sep 2026

AI Governance Frameworks for Privacy-Preserving Intelligent Systems: Integrating Trust, Compliance, and Secure Data Architectures

The analysis suggests that governance frameworks succeed when privacy-preserving technologies are embedded into system architecture from the outset rather than added afterward, when compliance obligations are translated into measurable technical requirements, and when trust is treated as an emergent property of verifia...

Hamed Taherdoost · 0 citations
#federated learning Review Open access Sep 2026

A Bibliometric Study of the Emerging Trends in Blockchain Research

The field of blockchain technology is continuously expanding and attracting more research interest. Blockchain promises decentralization, transparency, traceability, and resistance to censorship, all of which have prompted a heightened adoption in a wide range of sectors. We analyzed 57,116 papers published between 202...

Delia-Elena Bărbuță, Adrian Alexandrescu · 0 citations
#federated learning Open access Sep 2026

vantage6

Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains, and computation tasks are the journey. Vantage6 is complete...

Frank Joseph Martin, Bart van Beusekom, Richard Leurs et al. · 0 citations
#federated learning Open access Sep 2026

Uncertainty-Aware Dynamic Federated Vision Transformer for Skin Cancer Detection in Healthcare Environments

Initial public release of DynamicFedSkinCancerDetection. This release provides the implementation of the proposed Uncertainty-Aware Dynamic Federated Vision Transformer with Uncertainty-Guided Aggregation for skin cancer classification in a simulated federated learning environment. The implementation includes preproces...

Alassafi Madini O · 0 citations

Selecting AI Solutions for Managing False Information During Disasters: A Prescriptive Recommendation Framework

Social media has become an essential communication tool during disaster situations. Unfortunately, it is also used to spread false information very rapidly. This includes rumors, outdated or misleading information, doctored images, and fake news stories. These can undermine and disrupt public trust and emergency respon...

Jérémie Katembo Kavota, Daniel Tomiuk, Yasmeen ABUHASIRAH et al. · 0 citations
#federated learning Open access Sep 2026

vantage6

Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains, and computation tasks are the journey. Vantage6 is complete...

Frank Joseph Martin, Bart van Beusekom, Richard Leurs et al. · 0 citations
#federated learning Open access Sep 2026

vantage6

Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains, and computation tasks are the journey. Vantage6 is complete...

Frank Joseph Martin, Bart van Beusekom, Richard Leurs et al. · 0 citations
#federated learning Open access Sep 2026

A Review of Trust-Aware Explainable Federated Multimodal Learning for Early Cardiovascular Disease Prediction

Cardiovascular disease (CVD) is the largest cause of death worldwide, and artificial intelligence can now detect it earlier than traditional methods. The difficulty is that the data needed to train a reliable model is held separately by individual hospitals and is protected by privacy law. Federated learning (FL) answe...

Chandru K, D. Devakumari · 0 citations
#federated learning Open access Sep 2026

Federated learning in a regulator-audited secure processing environment: a multi-hospital deployment study

Background. Federated learning enables collaborative model development without transferring patient level data between institutions. However, translation into routine healthcare practice remains limited because deployment requires more than distributed model training. Federated infrastructures must operate within secur...

V. Nieminen, H. Schultze, S. Kukkurainen et al. · 0 citations
#federated learning Open access Sep 2026

vantage6

Vantage6 stands for privacy preserving federated learning infrastructure for secure insight exchange. The project is inspired by the Personal Health Train (PHT) concept. In this analogy vantage6 is the tracks and stations. Compatible algorithms are the trains, and computation tasks are the journey. Vantage6 is complete...

Frank Joseph Martin, Bart van Beusekom, Richard Leurs et al. · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 7, 2026

Discovering the value of humanistic inquiry

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.

Microsoft Research Blog Oct 7, 2026

Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses

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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