Uniform a priori bounds and error analysis for the Adam stochastic gradient descent optimization method

Uniform a priori bounds and error analysis for the Adam stochastic gradient descent optimization method explores Provides theoretical guarantees for the Adam optimizer, improving understanding of deep learning training.. Commercial viability score: 2/10 in LLM Training.