# Role of Pooling Layers in Convolutional Network Regularization

Understand how pooling layers introduces invariance, balancing equivariance and network efficiency.

Pooling brings “invariance” to a convolutional network. If a function is **invariant**, its output is unaffected by any translational change in the input.
A pooling operation draws a summary statistic from the convolution output. This replaces the overrepresentative convolution output with a single or a few summary statistics. Pooling, therefore, further regularizes the network and maintains its statistical efficiency.

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