OnConvergenceofAdamforStochasticOptimization underRelaxedAssumptions

Neural Information Processing Systems 

Wealsoprovidea probabilistic convergence result for Adam under a generalized smooth condition which allows unbounded smoothness parameters and has been illustrated empirically to capture the smooth property of many practical objective functions more accurately.

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