We use a variety of evaluation metrics to diagnose the effect that training with instance selection has on the learned distribution. In all cases where a reference distribution is required we usethe original training distribution,and not the distribution produced after instance selection. Inception Score (IS) [24] evaluates samples by extracting class probabilities from an ImageNet pretrained Inceptionv3 classifier and measuring the distribution of outputs over all samples. Classification Accuracy Score (CAS) [23, 25] was introduced for evaluating the usefulness of conditional generativemodels for augmenting downstream tasks such as image classification. Model Params (M) Batch Size Retention Ratio(%) IS FID P R D C BigGAN 52.54 512 100 25.43 10.55 - - - FQ-BigGAN 52.54 512 100 25.96 9.67 - - - - The truncation trick isasimple and popular technique which isused toincrease thevisual fidelity of samples from a GAN at the expense of reduced diversity [2].

The rise of Artificial Intelligence (AI) recently empowered researchers to investigate hard mathematical problems which eluded traditional approaches for decades. Y et, the use of AI in Universal Algebra (UA)--one of the fields laying the foundations of modern mathematics--is still completely unexplored.

Recent technological advances in systems neuroscience have led to a shift away from using simple tasks with low-dimensional, well-controlled stimuli towards trying to understand neural activity during naturalistic behavior.

Then, we propose a series of DP-SignRP algorithms that leverage the robustness of the "sign flipping probability" of random projections.