Convolutional networks may include local or global pooling layers^{[clarification needed]}, which combine the outputs of neuron clusters at one layer into a single neuron in the next layer.^[9][10] For example, max pooling uses the maximum value from each of a cluster of neurons at the prior layer.^[11] Another example is average pooling, which uses the average value from each of a cluster of neurons at the prior layer.

throwing away too much information

http://deeplearning.net/tutorial/lenet.html

http://ufldl.stanford.edu/tutorial/supervised/Pooling/