  Traditional statistical inference considers relatively small data sets and
the corresponding theoretical analysis focuses on the asymptotic behavior of a
statistical estimator when the number of samples approaches infinity. However,
many data sets encountered in modern applications have dimensionality
significantly larger than the number of training data available, and for such
problems the classical statistical tools become inadequate. In order to analyze
high-dimensional data, new statistical methodology and the corresponding theory
have to be developed.
