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AdaS&S: a One-Shot Supernet Approach for Automatic Embedding Size Search in Deep Recommender System
To address these challenges, we propose a novel one-shot AES framework called AdaS&S, in which a supernet encompassing various candidate embeddings is built and AES is performed as searching network architectures within it.
Situation-Aware Pedestrian Trajectory Prediction with Spatio-Temporal Attention Model
Pedestrian trajectory prediction is essential for collision avoidance in autonomous driving and robot navigation.
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