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Waymo & Google’s PolyLoss: Tailoring Loss Functions to Different Tasks and Datasets

Neural network training is based on a loss function, which can be any differentiable function that maps predictions and actual values at scale. When training a classification model, researchers typically turn to either cross-entropy or focal loss. But is there a way to design more flexible loss functions that can be tailored to different tasks and…

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