We invoke a basic lemma from the theory of so-called penalty methods of nonlinear programming to come up with a simple yet highly efficient block-adaptive training procedure that selects a suitable Weak Continuity (WC) regularization parameter by matching the complexity (`prior') of the resulting solution to that of a desired response. The matching is achieved using a simple binary search technique that is guaranteed to converge in very few steps; as such, it avoids many of the potential pitfalls of other iterative methods.
|Original language||English (US)|
|Number of pages||5|
|Journal||Conference Record of the Asilomar Conference on Signals, Systems and Computers|
|State||Published - Jan 1 1997|