Search Results for author:
Found 5 papers, 0 papers with code
Driving Digital Engineering Integration and Interoperability Through Semantic Integration of Models with Ontologies
This evolution requires new techniques to enhance design and analysis tasks that incorporate data integration and interoperability across various engineering tool suites spanning multiple domains at different abstraction levels.
A framework for fostering transparency in shared artificial intelligence models by increasing visibility of contributions
Increased adoption of artificial intelligence (AI) systems into scientific workflows will result in an increasing technical debt as the distance between the data scientists and engineers who develop AI system components and scientists, researchers and other users grows.
FLAP -- A Federated Learning Framework for Attribute-based Access Control Policies
The design of a policy transfer framework has challenges, including policy conflicts and privacy issues.
Cryptography and Security
Quantifying Transparency of Machine Learning Systems through Analysis of Contributions
Increased adoption and deployment of machine learning (ML) models into business, healthcare and other organisational processes, will result in a growing disconnect between the engineers and researchers who developed the models and the model's users and other stakeholders, such as regulators or auditors.
Federated AI for building AI Solutions across Multiple Agencies
The different sets of regulations existing for differ-ent agencies within the government make the task of creating AI enabled solutions in government dif-ficult.
