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Actual exam question for NVIDIA's NCA-GENM exam Question #: 302 Topic #: 1
During the training of a multimodal Generative A1 model, you observe that the gradients are vanishing, leading to slow convergence. Which of the following techniques can help mitigate the vanishing gradient problem?
ReLU and Leaky ReLU activation functions help prevent gradient saturation compared to Sigmoid functions. Gradient clipping limits the magnitude of gradients, preventing them from exploding and, indirectly, helping with vanishing gradients. Batch Normalization normalizes the activations, improving gradient flow. Skip connections allow gradients to flow more directly through the network, bypassing vanishing gradient issues. Sigmoid functions are known to exacerbate the vanishing gradient problem.
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