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1,995 papers
The adoption of data driven technologies in education has raised concerns about privacy, transparency and trust in centralized education systems. Artificial intelligence and learning analytics are used to personalized learning, however, their reliance on centralized data systems raises questions about privacy and secur...
The proliferation of Internet of Things (IoT) and Industrial Internet of Things (IIoT) technologies has fundamentally transformed contemporary computing infrastructures by interconnecting large heterogeneous devices, sensors, embedded systems, and cyber-physical platforms. These ecosystems support diverse applications...
Federated learning (FL) can train a shared model without pooling client records, but it does not by itself provide differential privacy (DP). We compare centralized training, local-only training, federated averaging (FedAvg), and client-level DP-FedAvg on a fully released synthetic benchmark of free-text root-cause-ana...
This chapter discusses mobile health (mHealth), teledermatology, and AI-based remote monitoring in the management of vitiligo. It investigates mHealth platforms based on CNNs and Vision Transformers to detect lesions and automatically score the severity of VASI/VETF with standardised photography protocols. The models o...
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This software and reproducibility package supports the study “Label-Induced Bias and Verification-Cost Trade-offs in Federated Learning: A Budget-Constrained Crowd-Intelligence Approach.” It contains source code, configuration information, analysis scripts, and final five-seed experimental outputs for federated learnin...
Federated learning (FL) enables collaborative maritime perception without transferring raw observations, but solar-powered clients must preserve energy for platform-specific duties. Existing energy-aware FL generally applies a common battery constraint and cannot jointly protect persistent buoy service and the safe ret...
Information and communication technologies (ICT) have become essential for delivering healthcare services in a faster, more accessible, and data-driven manner. At the same time, the growing scale of digital health data has raised concerns about privacy, security, and the effective use of distributed data sources. In th...
Artificial intelligence in medical imaging is becoming more common to improve clinical decision-making and accuracy of the diagnostic findings. Nevertheless, the high-level centralization of medical image storage and processing brings up serious challenges related to the privacy, security of data, regulatory advocacy,...
Decentralized learning ecosystems powered by blockchain, federated machine learning, and immersive metaverse environments are fundamentally reshaping educational data architecture and student engagement paradigms. This chapter presents a comprehensive investigation into AI-driven student performance prediction within t...
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...
Federated learning across device tiers that differ in sensing capability, using echo state networks with validation-gated aggregation and per-tier personalised readouts, evaluated on the PhysioNet/CinC Challenge 2021 ECG data.
Federated learning across device tiers that differ in sensing capability, using echo state networks with validation-gated aggregation and per-tier personalised readouts, evaluated on the PhysioNet/CinC Challenge 2021 ECG data.
Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.
A Blog post by NVIDIA on Hugging Face
A Blog post by IBM Research on Hugging Face
A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning.
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.
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.
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