The decomposition theory of matroids initiated by Paul Seymour in the 1980's has had an enormous impact on research in matroid theory. This theory, when applied to matrices ov...
Abstract. Hierarchical neural networks show many benefits when employed for classification problems even when only simple methods analogous to decision trees are used to retrieve t...
Rebecca Fay, Friedhelm Schwenker, Christian Thiel,...
Presynthesis optimizations transform a behavioral HDL description into an optimized HDL description that results in improved synthesis results. In this paper we introduce the decom...
Decision table decomposition is a machine learning approach that decomposes a given decision table into an equivalent hierarchy of decision tables. The approach aims to discover d...
Cylindrical algebraic decomposition is one of the most important tools for computing with semi-algebraic sets, while triangular decomposition is among the most important approache...
Changbo Chen, Marc Moreno Maza, Bican Xia, Lu Yang