Google says its AI tutor delivered a year of math progress in eight weeks. I asked the DeepMind researcher behind the trial ...
This tutorial introduces a comprehensive, clinically oriented, and compliance-aware framework integrating federated learning (FL) and blockchain for secure and privacy-preserving health care analytics ...
Abstract: When data privacy is imposed as a necessity, Federated learning (FL) emerges as a relevant artificial intelligence field for developing machine learning (ML) models in a distributed and ...
The rapid evolution of Intelligent Transportation Systems (ITS) and Autonomous Vehicles (AVs) has generated a massive influx of vehicular data. While this data is pivotal for enhancing traffic safety ...
Abstract: Over the past few years, significant advancements have been made in the field of machine learning (ML) to address resource management, interference management, autonomy, and decision-making ...
As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a ...
Since the introduction of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles in 2016, discussions have evolved beyond the original focus on research data to include learning ...
The integration of AI in digital healthcare has sparked immense optimism and transformative potential, particularly in the realms of patient care and medical research. This talk aims to provide a ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results