Understanding the Computational Complexity of Forward Propagation in Neural Networks
By
mathattack
Baker's choice. Dense with flavour, light on filler.
Summary
The article discusses the computational complexity of forward propagation in neural networks and the importance of understanding the procedure. It highlights the input vector, bias unit, and matrix dimensions in neural network implementation.
Key quotes
· 3 pulledFinding the asymptotic complexity of the forward propagation procedure can be done much like we found the run-time complexity of matrix multiplication.
When implementing neural networks, it's often the case that all the samples are collected into a matrix with the dimensions.
Why are neural networks so slow?
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