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CNN-based End-to-End Adaptive Controller with Stability Guarantees
This letter proposes a convolutional neural network (CNN)-based adaptive controller wtih three notable features: 1) it determines control input directly from historical sensor data (in an end-to-end process); 2) it learns the desired control policy during real-time implementation without using a pretrained network (in an online adaptive manner); and 3) the asymptotic tracking error convergence is proven during the learning process (to deliver a stability guarantee).
Towards User Friendly Medication Mapping Using Entity-Boosted Two-Tower Neural Network
Medication name inference is the task of mapping user friendly medication names from a free-form text to a concept in a normalized medication list.
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