Replacement Learning: Training Neural Networks with Fewer Parameters

Yuming Zhang, Peizhe Wang, Tianyang Han +5

End-to-end training with full-depth backpropagation remains the dominant paradigm for optimizing deep neural networks, but its efficiency deteriorates as models grow deeper. Since…