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Neural LoFi with Backward Coupling: A Spectral Theory of Cross-Layer Feature Learning
During joint training, backpropagation allows later layers to reshape earlier representations, a feedback mechanism absent from purely layer-wise learning. We extend Neural Low-Degree Filtering (Neural LoFi), a recently proposed layer-wise spectral surrogate for feature learning, to capture this int
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