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We recently proposed the Edgewise Greedy Algorithm (EGA) for learning a decomposable Markov network of treewidth k approximating a given joint probability distribution of n discrete random variables. The main ingredient of our algorithm is the stepwise forward selection algorithm (FSA) due to Deshpande, Garofalakis, and Jordan. EGA is an efficient alternative to the algorithm (HGA) by Malvestuto,...
Classification cascade is a well-known technique to reduce classification complexity (recognition time) while attaining high accuracy. While cascades are usually built using ad-hoc procedures, in this paper we introduce a principle way of building cascades using a greedy approach. Given a large pool of classifiers, our approach sequentially builds a near-to-optimal cascade. The approach is fully automated,...
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