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Learning Empirical Bregman Divergence for Uncertain Distance Representation
Deep metric learning techniques have been used for visual representation in various supervised and unsupervised learning tasks through learning embeddings of samples with deep networks.
Interpretability of Neural Network With Physiological Mechanisms
Deep learning continues to play as a powerful state-of-art technique that has achieved extraordinary accuracy levels in various domains of regression and classification tasks, including images, video, signal, and natural language data.
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