Self-supervised backprop and clustering

reconstruction

• If we force the hidden unit whose weight vector is closest to the input vector to have an activity of 1 and the rest to have activities of 0, we get clustering. – The weight vector of each hidden unit represents the center of a cluster. – Input vectors are reconstructed as the nearest cluster center.

data=(x,y)