• Calendar

November 26, Wednesday
12:00 – 13:30

We consider scenarios where a sequence of tests is to be applied to an object, where the result of a test may be that a decision (such as classification of the object) can be made without running additional tests. Thus, one seeks an ordering of the tests that is optimal in some sense, such as minimum expected resource consumption. Such sequences of tests are commonly used in computer vision cite{Viola2001} and other applications. We examine conditions under which one can efficiently find an optimal ordering of the tests. Two types of dependencies between tests are examined: ordering constraints, and statistical dependencies. We show that with dependencies the optimization problem is NP-hard in the general case, and provide low-order polynomial time algorithms for special cases with non-trivial constraint structures. (Patent pending)