Verified75% confidenceFactExact time
The core idea of backpropagation is to use the chain rule to decompose output error layer by layer, allowing the error signal to flow backward from the output layer to every weight parameter.
3
Sources
75%
Confidence
Long-term
Relevance
7/16/2026
First Seen
Sources
Related Claims
UnverifiedBackpropagation is essentially a systematic application of the chain rule, which efficiently computes the partial derivative of each parameter with respect to the loss function by propagating error signals layer by layer from the output layer to the input layer.81% similarVerified反向传播算法的本质是通过链式法则在计算图上高效计算标量损失对每个参数的偏导数80% similarVerifiedBackpropagation is essentially a dynamic programming algorithm for efficiently computing gradients, which reduces the computational complexity of gradient calculation by propagating error signals layer by layer from the output layer to the input layer and reusing intermediate computation results.80% similarVerifiedThe mathematical foundation of the backpropagation algorithm is the chain rule in calculus, which decomposes the gradient of a composite function into the product of local gradients at each layer, propagating the error signal layer by layer from the output layer to the input layer.79% similarVerifiedBackpropagation is the mathematical application of the chain rule.77% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/524083API
curl https://kongchang.com/api/v1/knowledge/claims/524083MCP
get_claim(id=524083)