exclude the compute spent in all the intermediate steps in getting to the final model such as experiments with architectures, hyper-parameter tuning, and model performance debugging. However, since the label_smoothing parameter in the CategoricalCrossentropy loss function, which you can easily set in your experiments. Yet another way of improving generalization is to allow the model to learn concepts in the order order of their difficulty. Curriculum learning shows us how. Curriculum Learning We know from experiments and machine learning theory that increasing the size of the dataset typically helps improve quality

can construct an arbitrary example and query an oracle for its label Learner can design and run experiments directly in the environment without any human guidance. Feng Li (SDU) Overview September 6, 2023

as the trained network. The signs of such a mask are chosen based on the trained weights. These experiments are yet to be replicated with the large networks. 11 Zhou, Hattie, et al. "Deconstructing lottery

d2l.plt.axhline(y=0.167, color='black', linestyle='dashed') d2l.plt.gca().set_xlabel('Groups of experiments') d2l.plt.gca().set_ylabel('Estimated probability') d2l.plt.legend(); 每条实线对应于骰子的6个值中的一个，并给出