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Non-Convex Optimization - Cornell University

Non-Convex Optimization - Cornell University

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•Let x 1, x 2 , …, x n be 1 if a i ... So non-convex optimization is pretty hard •There can’t be a general algorithm to solve it efficiently in all cases •Downsides: theoretical guarantees are weakor nonexistent •Depending on the application •There’s usually no theoretical recipe for setting hyperparameters

  Hard, Optimization

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