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The paper bridges two vast areas of research: stochastic team decision problems and convex stochastic programming. New methods developed in the latter are applied to the study of fundamental problems in the former. The main results are concerned with the Lagrangian relaxation of informational and material constraints in convex stochastic team problems.

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