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Titlebook: Combinatorial Optimization; Lectures given at th Bruno Simeone Conference proceedings 1989 Springer-Verlag Berlin Heidelberg 1989 algorithm

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31#
發(fā)表于 2025-3-27 00:50:02 | 只看該作者
32#
發(fā)表于 2025-3-27 02:56:55 | 只看該作者
Combinatorial structures and combinatorial optimization,
33#
發(fā)表于 2025-3-27 07:06:20 | 只看該作者
A polynomial algorithm for partitioning line-graphs,oblems, polynomial-time algorithms are available for special classes of graphs. In the present paper, the class of line-graphs is considered and a polynomial algorithm is proposed to solve both UGP and SMP in this class.
34#
發(fā)表于 2025-3-27 09:44:53 | 只看該作者
Structural dependence and systems of equations,he incidence matrix can be represented as a bipartite graph G=(X,Y,E), with the node sets partitioned into the sets X1, X2, Y1 en Y2, such that (a) there are no edges between X1 en Y2, and (b) the cardinality of X1+Y2 is maximum. Such a partition corresponds with the detection of complete and maxima
35#
發(fā)表于 2025-3-27 13:48:42 | 只看該作者
36#
發(fā)表于 2025-3-27 21:44:03 | 只看該作者
37#
發(fā)表于 2025-3-28 00:12:31 | 只看該作者
38#
發(fā)表于 2025-3-28 04:34:15 | 只看該作者
39#
發(fā)表于 2025-3-28 08:35:26 | 只看該作者
Evolutionspsychologische Bausteine,erlying Bayesian Network, it is capable of providing a comprehensible explanation of why a prediction is made. Furthermore, the runtimes of our learning algorithm are orders of magnitude lower than those state-of-the-art methods that are based on deep neural networks.
40#
發(fā)表于 2025-3-28 13:18:47 | 只看該作者
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