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What guarantees of optimality do we get when minimizing with Stochastic Gradient Descent a problem in its original formulation, after showing that it is a Geometric Programming instance (i.e. can be formulated as Convex Optimization when applying logarithmic transformation to the variables)?

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migrated from stats.stackexchange.com Jun 28 '18 at 18:00

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  • $\begingroup$ Cann you give more detail and context, please? And, without some connection to statistocs this would be better asked at math SE $\endgroup$ – kjetil b halvorsen Jun 28 '18 at 16:43

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