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Learning without Looking: Similarity Preserving Hashing and Its Potential for Machine Learning in Privacy Critical Domains
Machine Learning is frequently ranked as one of the most promising technologies in several application domains but falls short when the data necessary for training is privacy-sensitive and can thus not be used. We address this problem by extending the field of Privacy Aware Machine Learning with the application of ...
A Platform Framework for the Adoption and Operation of ML-based Smart Services in the Data Ecosystem of Smart Living
Smart services utilizing machine learning (ML) take a more and more important position in our daily lives. As a result, the need for a large smart living data ecosystem has emerged that links the most diverse areas of life with each other. This ecosystem is characterized by a multitude of different actors, a heterogeneous ...
Analyzing Smart Services from a (Data-) Ecosystem Perspective: Utilizing Network Theory for a graph-based Software Tool in the Domain Smart Living
There has long been a trend away from monolithic solutions toward integrated service systems that combine technical services and product functionalities across different manufacturers. This is especially true for the Smart Living domain, where interconnected products and services are used in one of the most private areas. ...
Service Tailoring: Ein Konfigurationsmechanismus für individualisierte After-Sales-Services im Maschinen- und Anlagenbau
Außerplanmäßige Instandsetzungen sind eine Herausforderung im Maschinen- und Anlagenbau. Dies betrifft sowohl Nutzer der Maschinen, die aufgrund der Ausfallzeit Abweichungen von ihren Produktionsplänen hinnehmen, aber auch Hersteller, die Serviceressourcen kurzfristig und dynamisch zuordnen müssen. Der Einsatz technischer ...
Towards the Operationalization of Trustworthy AI: Integrating the EU Assessment List into a Procedure Model for the Development and Operation of AI-Systems
Artificial intelligence (AI) is increasingly permeating all areas of life and not only changing coexistence in society for the better. Unfortunately, there is an increasing number of examples where AI systems show problematic behavior, such as discrimination or insufficient accuracy, missing data privacy or transparency. ...