federated learning

A particle swarm optimization-based layered personalized federated learning method for Non-IID data

Federated learning-enabled analytics for ESG data authenticity in digital apparel ecosystems: A platform governance perspective

VertiMosaic

A reproducible research framework for vertical federated learning on heterogeneous tabular data with explicit privacy boundaries, provenance and communication auditing.

appunuarni1975-spec/FedIoMT-RPM: FedIoMT-RPM v3.0: Lightweight adaptive split federated learning for patient-independent ECG arrhythmia classification

FedIoMT-RPM v3.0: Lightweight adaptive split federated learning for patient-independent ECG arrhythmia classification This release contains the complete code and final results for the revised manuscript submitted to Scientific Reports. It replaces v2.0. Main changes from v2.0 Patient-independent evaluation. All methods...

Performance changes in automated lesion detection under federated learning with sequential institution addition.

Sequential institution addition under FL may improve CAD software performance when combined with appropriate FT strategies, and FT that updates only a subset of layers may achieve performance changes comparable to those of FFT while requiring substantially fewer trainable parameters across different lesion detection ta...

🤖 NEURAL FOUNDATION MODELS, GENERALIZATION & PERSONAL REPRESENTATION AT THE LIMIT Foundation Models, Cross-Subject Transfer, Personal Neural Models, Brain-State Embeddings, Uncertainty, and the Emerging Science of Generalizable Neural Representation

🤖 NEURAL FOUNDATION MODELS, GENERALIZATION & PERSONAL REPRESENTATION AT THE LIMIT Foundation Models, Cross-Subject Transfer, Personal Neural Models, Brain-State Embeddings, Uncertainty, and the Emerging Science of Generalizable Neural Representation Can neural representations generalize without erasing individual biol...

AutoFL: System and Benchmark Suite

Source code, benchmark suite, and generated client files for the paper Schema-Augmented LLM Prompting for Converting ML Training Scripts to Federated Learning Clients (ACM TOSEM, resubmission 2026). v2.0 corrects FedAvg to sample-count weighting, partitions the IID simulation, moves generated-module import to preflight...

Rapport sur le déploiement du marché des fullerènes endohédraux Ag@C60

Résumé FRCe document, produit avec l’assistance de ChatGPT 5.2 Thinking et Gemini 3 Raisonnement, est publié sous licence Apache 2.0. Il constitue une publication défensive (antériorité) et entre de ce fait dans l’état de la technique au sens des législations applicables : EPC Art. 54(2); French IPC Art. L 611-11; cf....

A real-time federated TinyML framework for student behavior detection in smart classrooms

Smart classrooms increasingly require intelligent systems capable of detecting student behaviors in real time while preserving privacy and operating under limited computational resources. However, many existing approaches rely on centralized training and high-complexity deep learning models, limiting their suitability...

Blockchain-governed federated learning for IoT intrusion detection: training framework and ReputationManager smart contract

Reference implementation of a federated learning framework (FedAvg, FedProx, FedDyn) for IoT intrusion detection under a double non-IID client partition, together with the ReputationManager Solidity smart contract for on-chain client governance.

IA & Biotechnologies Multi-omiques pour la Santé, la Longévité et la Bioproduction

Abstract ENThis document, produced with the assistance of ChatGPT o3 and GPT-5 Thinking, is released under the Apache 2.0 licence. It is a voluntary defensive publication (prior art) and therefore enters the prior art upon release under the applicable patent statutes (art. L 611-11 CPI / art. 54(2) CBE; cf. 35 U.S.C. §...

NEURAL FOUNDATION MODELS, GENERALIZATION & PERSONAL REPRESENTATION AT THE LIMIT Foundation Models, Cross-Subject Transfer, Personal Neural Models, Brain-State Embeddings, Uncertainty, and the Emerging Science of Generalizable Neural Representation

🤖 NEURAL FOUNDATION MODELS, GENERALIZATION & PERSONAL REPRESENTATION AT THE LIMIT Foundation Models, Cross-Subject Transfer, Personal Neural Models, Brain-State Embeddings, Uncertainty, and the Emerging Science of Generalizable Neural Representation Can neural representations generalize without erasing individual biol...