The cost function for a low-dimensional representation
	• For points where pij is large and qij is small we lose a lot. – Nearby points in high-D really want to be nearby in low-D • For points where qij is large and pij is small we lose a little because we waste some of the probability mass in the Q distribution. – Widely separated points in high-D have a mild preference for not being too close in low-D. – But it doesn’t cost much to make the manifold bend back on itself.