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Title: Machine Learning in Digital Twin Edge Networks
Abstract:
In this talk, we mainly introduce our proposed new research
direction: Digital Twin Edge Networks (DITEN). We first present the
concept and model related to Digital Twin (DT) and DITEN. Then, we
focus on new research challenges and results when machine learning
is exploited in DITEN, including federated learing, deep
reinforcement learning and transfer learning. DT building, DT
placement and DT transfer as unique research questions, will be
defined and analyzed. We are also expecting that the talk will help
the audience understand the future development of edge computing,
e.g., digital twin edge networks in the context of Metaverse.
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