federated learning

Can Democracy Survive in a Hyperconnected World?

This paper explores the complex and often contradictory relationship between hyperconnectivity and democracy. Drawing on novel theoretical frameworks inspired by quantum mechanics, network science, and temporal dynamics, we argue that the hyperconnected world is not simply an extension of the classical political landsc...

Can Democracy Survive in a Hyperconnected World?

This paper explores the complex and often contradictory relationship between hyperconnectivity and democracy. Drawing on novel theoretical frameworks inspired by quantum mechanics, network science, and temporal dynamics, we argue that the hyperconnected world is not simply an extension of the classical political landsc...

Is the Algorithm an Epistemic Agent? A Critical Analysis of Computational Epistemology and the Emergence of Algorithmic Agency

The question of whether algorithms can be considered epistemic agents represents one of the most profound challenges at the intersection of philosophy of mind, epistemology, and artificial intelligence. This paper develops a novel theoretical framework for understanding algorithmic epistemic agency through the introduc...

Is the Algorithm an Epistemic Agent? A Critical Analysis of Computational Epistemology and the Emergence of Algorithmic Agency

The question of whether algorithms can be considered epistemic agents represents one of the most profound challenges at the intersection of philosophy of mind, epistemology, and artificial intelligence. This paper develops a novel theoretical framework for understanding algorithmic epistemic agency through the introduc...

Privacy-Preserving AI: Federated Learning, Differential Privacy, and Data Minimization: Production Architecture, Current Research, Real-World Use Case, Implementation, and Verification

Privacy-Preserving AI: Federated Learning, Differential Privacy, and Data Minimization: Production Architecture, Current Research, Real-World Use Case, Implementation, and Verification Author: Sonu Kumar Singh (Senior Consultant — Cloud & AI Solutions Architecture, Capgemini US LLC) Professional Affiliation: Capgemini...

marambhuvana-cpu/RobustTrust-FL: RobustTrust-FL v1.0.0

About RobustTrust-FL RobustTrust-FL is a trust-aware and attack-resilient federated learning framework for scalable privacy-preserving distributed intelligence. Key components PrivacyGuard: Privacy-preserving client updates using clipping and differential privacy. AttackShield: Detection of suspicious and potentially m...

Scaling limits of federated learning for vision-based road damage detection across countries

code for Adaptive and Explainable Federated Learning Framework for Robust Intrusion Detection in Heterogeneous and Adversarial IoT Environments

Big Data and Artificial Intelligence for Fintech Innovation Systematic Literature Review

Big Data Analytics (BDA) and Artificial Intelligence (AI) have emerged as key drivers of fintech innovation, enabling financial institutions to improve operational efficiency, risk management, customer services, and data-driven decision making. However, the growing literature remains fragmented, highlighting the need f...

Digital Sustainability Intelligence and Social Media Analytics: A Bibliometric Analysis

The combination of artificial intelligence (AI) and social media analytics provides the means to recognize and predict sustainability-related trends from large volumes of publicly available user data. Its adoption, however, is constrained by concerns about privacy, ethics, and transparency. This bibliometric study anal...

Privacy‐Preserving Federated Deep Learning for 6G Network Security Monitoring

Deep federated learning (DFL) has emerged as an effective paradigm for privacy‐preserving decentralized intelligence in sixth‐generation mobile networks. Increasing deployment of intelligent network services introduces challenges associated with high communication overhead, susceptibility to model poisoning attacks,...

Development of a geographic information mapping and dynamic monitoring platform for multi-network data fusion

To address governance bottlenecks such as data silos and fragmented monitoring in the implementation of the "Ten Networks" strategy in Xinjiang's Kezhou Prefecture, and to facilitate digital transformation in border regions, this paper conducts research on multi-network data integration, geographic information mapping,...