As the consequence of semantic gap, visual similarity does not guarantee semantic similarity, which in general is conflicting with the inherent assumption of many generativebased ...
We present a novel message passing algorithm for approximating the MAP problem in graphical models. The algorithm is similar in structure to max-product but unlike max-product it ...
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
Variance is a classical measure of a point estimator's sampling error. In steady-state simulation experiments, many estimators of this variance--or its square root, the stand...
Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...