Federated learning---training a shared model across many devices that never surrender their data---inverted machine learning's architecture: instead of data to the model, the model to the data. This article presents a narrative review of that arc's canonical line: Dwork and colleagues' 2006 differential privacy, Dwork...
Zen Revista, 10 IA· Zenodo (CERN European Organi...· 0 citations
Rapid evolution of cyber threats, cloud computing and digital transformation have led to increased need for adaptive and resilient cybersecurity framework. Zero Trust Architecture (ZTA) has been developed as an advanced security model that is designed to overcome limitations of the existing approaches based on perimete...
Loso Judijanto, R. Dewantara· West Science Information Sys...· 0 citations
An engineering-oriented deployment framework is proposed, integrating modality-driven model selection, structured preprocessing pipelines, multi-level clinical validation, computational feasibility assessment, and explainability, together with a clinical deployment readiness model spanning validation maturity, data div...
Enoch Jacob Dodo, Amos Takai Yayock, Gregory Onwodi et al.· Journal of Science Research...· 0 citations
Artificial intelligence (AI) has revolutionized medical imaging with automated disease detection, image segmentation, diagnosis, prognosis prediction, and clinical decision support across various imaging modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission...
S Sur, Mandal Rakesh Kumar, Chanda Debanil· Zenodo (CERN European Organi...· 0 citations
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Artificial intelligence (AI) has revolutionized medical imaging with automated disease detection, image segmentation, diagnosis, prognosis prediction, and clinical decision support across various imaging modalities, such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), ultrasound, positron emission...
S Sur, Mandal Rakesh Kumar, Chanda Debanil· Zenodo (CERN European Organi...· 0 citations
This survey develops a unified taxonomy that systematically integrates learning paradigms, agent architectures, coordination mechanisms, deployment models, application domains, and evaluation frameworks from a common analytical perspective and provides a structured foundation for future advances in intelligent agent sy...
Elias Dritsas, M. Trigka· Evolutionary Intelligence· 0 citations
AF-EdgeRL is proposed, a novel Byzantine-resilient Asynchronous Federated Reinforcement Learning framework tailored for distributed resource allocation and dynamic task offloading and establishes theoretical convergence guarantees under non-convex reinforcement learning objectives.
Daniel Merrow, Tember L. Nair, Lucas Farnandez· International Journal of App...· 0 citations
Executive Overview This consolidated release of Paper X unifies empirical findings, mathematical foundations, and real-world implementation proofs for AuraOS—a local-first, zero-extraction computational architecture designed to eliminate recurring cloud SaaS overhead and API token extraction. By decoupling spatial reco...
Dallas Courchene· Zenodo (CERN European Organi...· 0 citations
Clinical modeling experience is established as a promising collaborative object beyond conventional parameter-centric FL and point toward federated autonomous clinical intelligence.
Reproducibility capsule for FusionNet Lite, a lightweight sequence-fusion deep-learning pipeline for predictive maintenance in industrial IoT systems. The campaign evaluates FusionNet Lite alongside CNN, BiLSTM, MLP, and CNN-LSTM baselines using centralized and FedAvg federated training across five seeds. The capsule i...
Federated learning (FL) offers a promising approach to training machine learning models on decentralized data sources without directly exchanging data. However, traditional FL methods often rely on a central server, raising significant privacy concerns, especially when dealing with sensitive data residing on edge devic...
Jincheng Zhang· Zenodo (CERN European Organi...· 0 citations
Acute lateral ankle sprain is among the most frequent injuries in sports medicine, and its high recurrence rate and propensity toward chronic ankle instability (CAI) constitute a persistent clinical challenge. Conventional risk assessment—relying on subjective questionnaires, physical examination, and clinical experien...
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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