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Found 2 papers, 1 papers with code
Few-shot Classification via Ensemble Learning with Multi-Order Statistics
To address this need, we prove theoretically that leveraging ensemble learning on the base classes can correspondingly reduce the true error in the novel classes.
Self-Supervised Music-Motion Synchronization Learning for Music-Driven Conducting Motion Generation
Therefore, we propose a novel Music Motion Synchronized Generative Adversarial Network (M2S-GAN), which generates motions according to the automatically learned music representations.
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