Skip to content
Log in
Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Category

federated learning

1,836 papers

#federated learning Open access Aug 2026

Federated Learning Architectures For Privacy-Preserving Customer Intelligence Across Telecom Networks

This paper presents a privacy-by-design federated learning reference architecture for customer intelligence across telecom networks, in which each operator trains locally on its own CRM, billing, service-interaction, and network-telemetry data and shares only encrypted model updates, never raw records.

Brahmananda Naidu Dabbara · 0 citations
#federated learning Jul 2026

ProMoE-FL: Prototype-conditioned Mixture of Experts for Multimodal Federated Learning with Missing Modalities

ProMoE-FL, a Prototype-conditioned Mixture-of-Experts framework for robust missing-modality feature synthesis in multimodal federated learning with missing modality, builds a global client-aware prototype bank that captures clinically meaningful modality priors across institutions.

Aavash Chhetri, Bibek Niroula, Eduard Vazquez et al. · 0 citations
#federated learning Review Open access Aug 2026

From Reactive to Proactive Healthcare: Synergizing Wearable Biomarkers and Machine Learning in Digital Therapeutics

This paper synthesizes the latest literature on the intersection of mobile health, machine learning, and physiological tracking, with a primary focus on heart rate variability (HRV) and associated biochemical markers, such as cortisol, salivary alpha-amylase, and interleukins.

Kwanjoon Park, Eunice Kwan Chae Park, W. Park et al. · 0 citations
#federated learning Open access Nov 2026

FLEAT: Energy-Accuracy Trade-Off in Federated Learning Over Heterogeneous Edge Devices

This work proposes FLEAT (Federated Learning Energy and Accuracy Tuning), a framework that jointly optimizes energy efficiency and model accuracy via dynamic local update adaptation and gradient-informed layer-wise pruning, offering a scalable solution for energy-accuracy equilibrium in heterogeneous FL deployments.

Javad Dogani, Reza Namvar, Masoumeh Khodarahmi et al. · 0 citations
#federated learning Open access Aug 2026

An Explainable AI-Driven Cyber Threat Intelligence Framework for Proactive and Adaptive Cyberattack Detection

XAI-CTI is presented, a novel Explainable Artificial Intelligence (XAI)-driven Cyber Threat Intelligence (CTI) framework designed to enable proactive and adaptive cyberattack detection that achieves state-of-the-art detection accuracy and reduces analyst investigation time.

R. Yadav · 0 citations
#federated learning Open access Aug 2026

AuraOS Paper X Rev.3: A Regenerative, Model-Orthogonal, Source-Bound Cognitive Operating Substrate - Relational World Compilation, Coordinate Memory, HyperScale/ HyperDrive, Runtime Arenas, Proof-Carrying Commons, Recursive Swarms, Universal Host Compilation, and Semantic-Spatial Interfaces

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 · 0 citations
#federated learning Open access Aug 2026

A Quantum-Resilient Federated Learning Framework for Secure Smart Grid

Wide-area monitoring systems built on phasor measurement units (PMUs) underpin real-time stability assessment in transmission grids, yet their measurement and communication paths present an attack surface that conventional intrusion detection addresses only partially. Three constraints compound the problem: transmissio...

Divyam Tank, Dr. Sushil Kumar Singh · 0 citations
#federated learning Open access Aug 2026

A Quantum-Resilient Federated Learning Framework for Secure Smart Grid

Wide-area monitoring systems built on phasor measurement units (PMUs) underpin real-time stability assessment in transmission grids, yet their measurement and communication paths present an attack surface that conventional intrusion detection addresses only partially. Three constraints compound the problem: transmissio...

Divyam Tank, Dr. Sushil Kumar Singh · 0 citations
#federated learning Review Open access Aug 2026

Learning Where the Data Lives: A Narrative Review of Federated Learning from Differential Privacy to the Open Problems

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 · 0 citations
#federated learning Review Open access Aug 2026

Learning Where the Data Lives: A Narrative Review of Federated Learning from Differential Privacy to the Open Problems

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 · 0 citations
#federated learning Open access Aug 2026

Zero Trust Architecture Research Trends: A Bibliometric Study

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 · 0 citations
#federated learning Review Open access Aug 2026

Artificial Intelligence for Medical Imaging Diagnosis: From Accuracy to Clinical Reliability through Multimodal Fusion, Validation, and Regulatory Perspectives

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. · 0 citations

From tech blogs

See all →
Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

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 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.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.