Reducing Pseudo-Gradient Uncertainty with Larger Sample Sizes

Obviously, increasing the sample size can gradually reduce the variance of the pseudo-gradient uncertainty. This is a common practice in machine learning to improve the accuracy and reliability of model training. By increasing the sample size, we provide the model with more data points to learn from, which helps to reduce the impact of random noise and outliers in the data. This results in a more stable and accurate estimate of the gradient, leading to a lower variance of the pseudo-gradient uncertainty.