We've provided a webpage for our dataset, which contains a link to the dataset. Our dataset is currently available through our webpage (and directly via this link). We use a learning rate of 0.01 for ResNet-18 and0.1forResNet-50. This loss is motivated by recent contrastive learning to maximize the probability for the neural network to select the corresponding patch in both the original imagexI and the generated image ˆxI. For reference, we also show the image that corresponds to the tactile example at rightmost (not used by the model).

Toaudit filteringinformation usersees frequent, "similarity" Suppose T (e.g., Suppose F generates Z of T when givenx0. RecallfromF complies F is decision-rob F isguaranteed ontheroleof 4.1 Guarantee Theorem 1.Consider(1).

Priorworkhastackledthisissue ways (see Section 5).

Although the fairness community has recognized the importance of data, re-searchers inthe area primarily rely on UCIAdult when itcomes totabular data.