Verified80% confidenceFactExact time
The essence of backpropagation is chain-rule differentiation, where the gradient of the loss function with respect to the parameters of each layer is propagated layer by layer from the output layer to the input layer, on the premise that the loss function must exist and be differentiable.
4
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80%
Confidence
Long-term
Relevance
7/8/2026
First Seen
Sources
基准测试即数据激活：让领域数据找到攀登方向
hackernewshackernews7/3/2026
Related Claims
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