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federated learning

1,703 papers

#federated learning Open access Dec 2026

FLInterrupt: An interactive federated learning simulator for client interruption experiments

We introduce FLInterrupt, an open-source, browser-based federated learning (FL) simulator for research on involuntary client interruption during synchronous FedAvg. The backend runs communication rounds in PyTorch. A React dashboard lets researchers set datasets and models, interrupt or reconnect clients at runtime, re...

Tudor-Mihai David, Mihai Udrescu · 0 citations
#federated learning Open access Oct 2026

Practical Byzantine-Resilient Federated Learning via Zero-Knowledge Proofs and Adaptive Reputation

Trust management under adversarial uncertainty is a central challenge in distributed learning systems. We propose Verifiable FL with Two-Stage Selection (VFL-TS), a knowledge-driven framework for Byzantine-resilient federated learning that maintains a dynamic trust knowledge base—updated through cryptographically verif...

Omar Dib · 0 citations
#federated learning Open access Oct 2026

Lifelong-IDS

Federated Learning (FL) enables collaborative intrusion detection across distributed Internet of Things (IoT) edge devices without centralizing private network telemetry. However, existing frameworks assume static data distributions and fail under non-stationary conditions: emerging zero-day attack families cause sever...

AlHayan Abdullah · 0 citations
#federated learning Open access Oct 2026

Privacy-Preserving Federated Remote Sensing via Spatially Modulated Feature Perturbation and Ground Alignment

Space-to-ground collaborative remote sensing has become a promising mode for global-scale earth observation. However, the open satellite-ground communication link faces severe security threats, especially when unauthorized eavesdroppers deploy gradient or feature inversion attacks based on deep learning to reconstruct...

Kun Wang, Yuan Gao, Yuanqiao Zhang et al. · 0 citations
#federated learning Book Oct 2026

AI-Driven Learning Analytics for Personalized STEAM Education

The AI-based learning analytics is revolutionizing STEAM learning by facilitating adaptable, information-based, and individualised learning space. The chapter discusses the application of machine learning, natural language processing and predictive analytics to multimodal data on learners to create dynamic learner prof...

Shilpa Aarthi, R. N. Ravikumar · 0 citations
#federated learning Book Open access Oct 2026

THE EL-RAKHAWI ARCHITECTURE FOR PREDICTIVE BIOSENSING AND PRECISION THERAPEUTICS (EAPBPT) A Mathematically Provable, Clinically Validated Framework for Pre-Symptomatic Disease Detection, AI-Driven Diagnosis, and Pharmacogenomically Optimized Treatment

The El-Rakhawi Architecture for Predictive Biosensing and Precision Therapeutics (EAPBPT) by Dr. Mohamed Kamal Arafa El-Rakhawi (DOI: 10.5281/zenodo.23084200) integrates six validated technologies for pre-symptomatic disease detection and personalized treatment: multi-omic liquid biopsy, lab-on-a-chip microfluidics, we...

m el-rakhawi · 0 citations
#federated learning Open access Oct 2026

Federated Learning in Healthcare Data Analytics: A Privacy-Preserving Approach

The rapid digitization of healthcare has led to an explosion of patient data, necessitating advanced analytics for improved diagnostics, treatment, and predictive modeling. However, traditional centralized data processing poses significant privacy and security risks, particularly concerning sensitive patient informatio...

Olabode Michael Soneye · 0 citations
#federated learning Open access Oct 2026

Practical Byzantine-Resilient Federated Learning via Zero-Knowledge Proofs and Adaptive Reputation

Trust management under adversarial uncertainty is a central challenge in distributed learning systems. We propose Verifiable FL with Two-Stage Selection (VFL-TS), a knowledge-driven framework for Byzantine-resilient federated learning that maintains a dynamic trust knowledge base—updated through cryptographically verif...

Omar Dib · 0 citations
#federated learning Open access Oct 2026

Reducing Clinician Annotation Fatigue in Open-Set Federated Learning: A Client-Adaptive Vision-Language Gatekeeper.

PURPOSE Federated learning enables breast-imaging sites to jointly train mammography artificial intelligence (AI) without sharing images, but radiologists at each site must still annotate selected images during active-learning rounds. We developed and evaluated a client-adaptive vision-language gatekeeper that withhold...

Adea Nesturi, D. Gaviria, Jia-Jun Zeng 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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