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Exploiting Phoneme Similarities in Hybrid HMM ANN Keyword    Publications Idiap  Form

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hello everyone Welcome to our promot video highlighting our work titled decentralized Collaborative Learning with adaptive reference data for UND device P recommendation traditional cloud-based recommendation systems involve collecting personal data like cck history front devices training models on the cloud and sending recommendation results back to devices while this ensures accuracy it raises privacy concerns since users sensitive behaviors are collected from their devices moreover it has limited us abilities due to network latency and traffic therefore UND devis recommendations have gathered attention one approach is centralized learning as implemented in federa recommendation users are trained locally based on their private data and then send the knowledge to the Cloud Server the Cloud Server Aggregates alled models and redistributes them to the users device side however centralized servers are heavily relied upon throughout the training process and have limitations on abilities s

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