5-min reads: why propogation cell state through mini-batches slows convergence
learning a neural network from the inside out
In this 5-min read I’ll try to explain how convergence can be slower for LSTM neural networks where memory state is maintained from one mini-batch to the next. An example of this problem can be found in my project about a microsleep detector