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In computability and complexity, finding mappings between problems that allow solving one problem using a solution of another one. For reduction in programming language theory (e.g. beta-reduction), see [lambda-calculus] or [term-rewriting].

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Show that finding a minimum-weight subgraph that includes all marked nodes is NP-hard

We've been given a weighted graph with marked nodes. We want to make a minimum-weight subtree from this graph that contains all marked nodes. I want to show that this problem is NP-hard. Is there any …
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Show that finding a minimum-weight subgraph that includes all marked nodes is NP-hard

I think vertex cover can be easily used when we consider edges as nodes and mark only those nodes that has a correspend edge in G. I think it will work
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