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Federated learning (also known as collaborative learning) is a machine learning technique focusing on settings in which multiple entities (often referred to as clients) collaboratively train a model while ensuring that their data remains decentralized. [1]
FLoC in Google Chrome components. The Federated Learning of Cohorts algorithm analyzes users' online activity within the browser, and generates a "cohort ID" using the SimHash algorithm [13] to group a given user with other users who access similar content.
Federated learning, a machine learning technique; Federated protocol, in networking, the ability for users to send messages from one network to another; Federated architecture, a pattern in enterprise architecture; Federated search, a type of electronic search; Federated database system, a type of meta-database management system
Federated learning is an adapted form of distributed artificial intelligence to training machine learning models that decentralizes the training process, allowing for users' privacy to be maintained by not needing to send their data to a centralized server. This also increases efficiency by decentralizing the training process to many devices.
With federated learning coupled with local differential privacy, researchers have found this model to be quite effective to facilitate crowdsourcing applications and provide protection for users' privacy. Federated learning has the ambition to protect data privacy through distributed learning methods that keep the data in its storage. Likewise ...
Federated Enterprise Architecture is a collective set of organizational architectures (as defined by the enterprise scope), operating collaboratively within the concept of federalism, in which governance is divided between a central authority and constituent units balancing organizational autonomy with enterprise needs.
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Trustworthy AI is also a work programme of the International Telecommunication Union, an agency of the United Nations, initiated under its AI for Good programme. [2] Its origin lies with the ITU-WHO Focus Group on Artificial Intelligence for Health, where strong need for privacy at the same time as the need for analytics, created a demand for a standard in these technologies.