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, …) are showing serious limitations, especially in view of the increased complexity of communication networks. Research on machine learning (ML) applied to communications is currently attracting incredible interest
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through various sensors and actuators (smart cities, autonomous vehicles, and industrial robots, etc.). Machine Learning (ML) subsystems have been proposed for some of their core components (e.g., process
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economic viability analysis (Industrial track: IMT + Séché R&D) Topic 2: Integration of Reconfigurable Intelligent Surfaces and Machine Learning over THz Bands towards Future 6G Networks (co-tutelle/academic
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will be exposed to top level researchers in the fields of medicine (Brest CHRU), algorithmics (ERC holder at Politecnico di Torino), machine learning (ERC holder in the LaTIM), bio-engineering (EPFL) as
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Transformation (MT) languages have a natural application in the data integration step. Machine Learning (ML) techniques are instead prominently used for data inference, after training on historical traces