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This section delves into the field of FL, a method created to produce accurate models while protecting the privacy of people and institutions. As mentioned, it proposes a collaborative learning paradigm in which numerous devices take part in training a shared model under the direction of a central server. This section investigates the nuances of this collaboration procedure and its various architectural strategies.
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