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ICLR 2020: Yann LeCun and Energy-Based Models

Machine Learning Street Talk (MLST)

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Exploring Siamese Networks and Energy Functions in Image Recognition

This chapter explores advanced image recognition methods, particularly Siamese networks and triplet loss, as well as comparing traditional techniques such as DeepFace and FaceNet with innovative contrastive learning approaches. The discussion also addresses challenges in training models, including negative mining strategies and the incorporation of energy functions in the encoding process.

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