A framework based on cost amortization and local approximation gives constant-factor approximation algorithms for combinatorial selection with costly information under matroid constraints.
Maximizing stochastic monotone submodular functions
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Combinatorial Selection with Costly Information
A framework based on cost amortization and local approximation gives constant-factor approximation algorithms for combinatorial selection with costly information under matroid constraints.