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On the influence of stochastic rounding bias in implementing gradient descent with applications in low-precision training – Lu Xia (Eindhoven University of Technology)

In the context of low-precision computation for the training of neural networks with thegradient descent method (GD), the occurrence of deterministic rounding errors often leadsto stagnation or adversely affects the convergence of the optimizers.…

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