Channels ▼   Sizing Samples: How Much Data Is Enough?  Across
science and engineering, computers are often enlisted to find
patterns in data. The data might be genetic information about a
population, and the pattern could be which gene variants
predispose people to asthma. Or the data might be frames of
video, and the patterns could be objects that move or stand
still from frame to frame, which data-compression or image-
sharpening algorithms might want to locate.  In most cases, more
data means more reliable inference of patterns. But how much
data is enough? Vincent Tan, a graduate student in MIT's
Department of Electrical Engineering and Computer Science, and
his colleagues in Alan Willsky's Stochastic Systems Group have
taken steps toward answering that question.  Tan, Willsky and
Animashree Anandkumar, a postdoc in Willsky's group, envision
data sets as what mathematicians call graphs. A graph is
anything with nodes and edges: Nodes are generally depicted as
circles and edges as lines connecting them. A t