Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Zipperling, Domenique"'
Federated Learning presents a way to revolutionize AI applications by eliminating the necessity for data sharing. Yet, research has shown that information can still be extracted during training, making additional privacy-preserving measures such as d
Externí odkaz:
http://arxiv.org/abs/2408.08666
In the landscape of generative artificial intelligence, diffusion-based models have emerged as a promising method for generating synthetic images. However, the application of diffusion models poses numerous challenges, particularly concerning data av
Externí odkaz:
http://arxiv.org/abs/2406.14429
The topic of fairness in AI, as debated in the FATE (Fairness, Accountability, Transparency, and Ethics in AI) communities, has sparked meaningful discussions in the past years. However, from a legal perspective, particularly from the perspective of
Externí odkaz:
http://arxiv.org/abs/2403.20089
In the landscape of generative artificial intelligence, diffusion-based models present challenges for socio-technical systems in data requirements and privacy. Traditional approaches like federated learning distribute the learning process but strain
Externí odkaz:
http://arxiv.org/abs/2402.19105
Data analysis plays an indispensable role for value creation in industry. Cluster analysis in this context is able to explore given datasets with little or no prior knowledge and to identify unknown patterns. As (big) data complexity increases in the
Externí odkaz:
http://arxiv.org/abs/2106.12792