Pooling (machine learning)
Reducing a matrix (or matrixes) created by an earlier convolutionary layer to a smaller matrix. Pooling usually involves taking either the maximum or average value across the pooled area.1
Pooling for vision applications is known more formally as spatial pooling. Time-series applications usually refer to pooling as temporal pooling. Less formally, pooling is often called subsampling or downsampling.1