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This paper analyzes generalization error, uniform stability, and uniform argument stability of gradient descent (GD) and stochastic gradient descent (SGD) over discrete parameter spaces with deterministic or stochastic rounding, showing that rounding degrades generalization for GD and introduces dimension-dependent errors for stochastic rounding.