In this paper, we propose a recursive method for structural learning of directed acyclic graphs (DAGs), in which a problem of structural learning for a large DAG is first decompos...
Abstract. We present an algorithm for automatically constructing a decompositional shape model from examples. Unlike current approaches to structural model acquisition, in which on...
Alex Levinshtein, Cristian Sminchisescu, Sven J. D...
Abstract. In the last decades, the Satisfiability and Constraint Satisfaction Problem frameworks were extended to integrate aspects such as uncertainties, partial observabilities, ...
Local ratio is a well-known paradigm for designing approximation algorithms for combinatorial optimization problems. At a very high level, a local-ratio algorithm first decomposes ...
concerns, abstraction (particularly hierarchical abstraction), simplicity, and restricted visibility (locality of information). The overall goal behind these principles was stated ...