This study aimed to determine the implementation of memorizing Al-Qur'an at MAN 2 Palembang. The type qualitative writing approach used in this uses a descriptive approach, meaning that data collected is not form numbers but instead interview scripts, field notes, and pictures. authors use collection methods like observation, interviews, documentation obtain accurate data. analysis by writer re...

It can be difficult to tell whether a trained generative model has learned to generate novel examples or has simply memorized a specific set of outputs. In published work, it is common to attempt to address this visually, for example by displaying a generated example and its nearest neighbor(s) in the training set (in, for example, the L metric). As any generative model induces a probability de...

We propose an approach to address two undesired properties of unsupervised GANs. First, since GANs use only a continuous latent distribution to embed multiple classes or clusters of a dataset, GANs often do not correctly handle the structural discontinuity between disparate classes in a latent space. Second, discriminators of GANs easily forget about past generated samples by generators, incurr...

2 Details of the pathological synthetic problems 3 2.1 The addition, multiplication, and XOR problem . . . . . . . . . . . . 3 2.2 The temporal order problem . . . . . . . . . . . . . . . . . . . . . . 4 2.3 The 3-bit temporal order problem . . . . . . . . . . . . . . . . . . . . 4 2.4 The random permutation problem . . . . . . . . . . . . . . . . . . . 4 2.5 Noiseless memorization . . . . . . ...

Deep Neural Networks (DNNs) are increasingly being used in software engineering and code intelligence tasks. These powerful tools that capable of learning highly generalizable patterns from large datasets through millions parameters. At the same time, their capacity can render them prone to memorizing data points. Recent work suggests memorization risk manifests especially strongly when trainin...