Figure 2: Curricula influence the learning efficacy of the Vanilla CL algorithm (Sec 3.2) across MNIST, FashionMNIST, and CIFAR10 datasets (Sec 3.1).

We trained the vanilla CL algorithm on all curricula from each dataset. Each dot represents one curriculum. We report the distribution of average accuracy $\alpha$ over all the seen classes (left panel, Sec 3.3) and the distribution of forgetfulness $\beta$ at the last task (right panel, Sec 3.3). We introduced $ℱ$ as the measure of the learning efficacy of a given curriculum (Sec 3.3). See the colorbar on the right for different $ℱ$ values. Note that the y-axis does not carry any meaning. All the dots are randomly spread along the y-axis for easy visualization of the $\alpha$ and $\beta$ distributions.