function in Figure 2 scores instances based on their frequency of occurrence in the hard batch.
for each instance h i : where S e (h i ) is the score of h i at iteration e, 1 Y (x) is an indicator function which is 1 when x ∈ Y and otherwise 0, hard batch e indicates the set of hard instances at iteration e, and loss e (h i ) is the loss of the network for h i at iteration e. The above function assigns higher scores to instances that are frequently considered as hard instances by the curriculum learning framework (such instances are ranked higher in the final ranked list of spurious instances).