Evaluation of Neural Architectures Trained with Square Loss vs Cross-Entropy in Classification Tasks

Modern neural architectures for classification tasks are trained using the cross-entropy loss, which is widely believed to be empirically superior to the square loss. In this work we provide evidence indicating that this belief may not be well-founded... (read more)

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