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Near-OptimalLowerBoundsForConvex OptimizationForAllOrdersofSmoothness
Neural Information Processing Systems
We study the complexity of optimizing highly smooth convex functions.
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Onthe Stabilityand Scalabilityof Node Perturbation Learning
Neural Information Processing Systems
Then, minimaxn, denoted , is isthenumbern is numberofdislarge, one. F, and down learning ofthe Scalability Eq. 11).Lh L initialization 37] and described a=co F is norm, co isa dynamical anddotted time.
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