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federated learning

1,995 papers

#federated learning Review Open access Oct 2026

The Changing Landscape of Plant Disease Detection: The Role of Artificial Intelligence

Plant diseases constrain agricultural productivity and food security, while conventional diagnosis depends heavily on visible symptoms and specialist expertise, limiting rapid and scalable assessment across heterogeneous agricultural environments. Artificial intelligence (AI), particularly machine learning, deep learni...

Aksa Anna Shajan, Sumiya K. V., S. Kurian P et al. · 0 citations
#federated learning Open access Oct 2026

song1741008932-ship-it/FedDWM: v1.2

FedDWM: A Dynamic Watermark Migration Framework for Model Poisoning Defense in Federated Learning

song1741008932-ship-it · 0 citations
#federated learning Open access Oct 2026

Securing the open-source ecosystem: AI-enhanced and explainable supply chain security for reliable software development

Modern software supply chains face increasing risks from vulnerable and anomalous dependencies, necessitating automated and interpretable detection methods integrated within Continuous Integration and Continuous Deployment (CI/CD) workflows. Open-source software (OSS) ecosystems are increasingly targeted by sophist...

A. Alzahrani, Muhammad Zubair Asghar · 0 citations
#diffusion models Open access Oct 2026

Cadre Stratégique pour l'Infrastructures Immobilière Éco-Résilience : Déclaration d'Antériorité Complète et Divulgation Habilitante

Résumé FRCe document, produit avec l’assistance de Gemini 3 Raisonnement, est publié sous licence Apache 2.0. Il constitue une publication défensive volontaire (antériorité) et entre de ce fait dans l’état de la technique au sens des législations applicables : art. L 611-11 CPI (Code de la propriété intellectuelle fran...

Xavier Pillet · 0 citations
#diffusion models Open access Oct 2026

Cadre Stratégique pour l'Infrastructures Immobilière Éco-Résilience : Déclaration d'Antériorité Complète et Divulgation Habilitante

Résumé FRCe document, produit avec l’assistance de Gemini 3 Raisonnement, est publié sous licence Apache 2.0. Il constitue une publication défensive volontaire (antériorité) et entre de ce fait dans l’état de la technique au sens des législations applicables : art. L 611-11 CPI (Code de la propriété intellectuelle fran...

Xavier Pillet · 0 citations
#federated learning Open access Oct 2026

Саморегульований центр операцій безпеки на основі федеративного навчання з постквантовими механізмами захищеної агрегації

Objective. The objective of the research is to develop an architecture for a self-regulating Security Operations Center (SOC) that ensures autonomous adaptation of agents to new threats by combining federated learning with post-quantum secure model aggregation mechanisms based on lattice cryptography, while simultaneou...

Євген Живило, Аліна Янко, Yurii Kuchma et al. · 0 citations
#federated learning Book Oct 2026

AI-Driven Predictive Modeling for Personalized Vitiligo Treatment and Patient Stratification

Vitiligo is hard to personalize because disease activity, anatomical response, immune persistence, and repigmentation capacity vary widely across patients. This chapter proposes a precision-medicine framework integrating longitudinal clinical data, standardized imaging, patient-reported outcomes, biomarkers, transcript...

Mohammad Ali Al Khaldy, Ahmad Al-Tarawneh · 0 citations
#federated learning Open access Oct 2026

Self-evolutionary control architecture based on distributed brain-inspired decision making and privacy-preserving PID

Traditional PID control suffers from limited parameter adaptability in complex dynamic systems and poor robustness against nonlinearities and uncertain disturbances. Meanwhile, in distributed power control scenarios, the risk of leakage regarding multi-node sensor data and AI model parameters hinders the practical impl...

Ming-Zhe Hou, Zi-Jun Liu, Qi-Shen Lv · 0 citations
#federated learning Open access Oct 2026

FedStaP: Shared Feature Statistics and Prior-Calibrated Training for Non-IID Federated Intrusion Detection in IoT Networks

Federated learning allows IoT gateways to train a shared intrusion detector without exporting traffic records, but gateways observe different attack classes and scale their flow features differently. Stateful optimisers such as SCAFFOLD correct the resulting client drift at the cost of per-client memory and twice the p...

Ahmed Fahad, Mohammed F. Alomari, Yazan Aljeroudi · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 23, 2026

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

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

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