Dropout is typically interpreted as bagging a large number of models sharing parameters. We show that using dropout in a network can also be interpreted as a kind of data augmentation in the input space without domain knowledge. We present an approach to projecting the dropout noise within a network back into the input space, thereby generating augmented versions of the training data, and we sh...

In this paper, a low dropout (LDO) circuit based on curvature compensation benchmark and closed-loop stability is designed. This compensates for the higher order term of VBE in BJT through subthreshold characteristic MOSFET achieves effect compensation. The bandgap reference provides stable input voltage LDO circuit, while source follower adaptive bias improve response speed circuit. temperatur...

STUDY QUESTION What are the dropout rates in lifestyle intervention programs (LIPs) for overweight and obese infertile women and can intervention- or patient-related baseline factors associated with dropout be identified in these women? SUMMARY ANSWER The median dropout rate was 24% in overweight and obese infertile women who participated in a LIP; clinical useful intervention or patient-rela...

Dropout has recently emerged as a powerful and simple method for training neural networks preventing co-adaptation by stochastically omitting neurons. is currently not grounded in explicit modelling assumptions which so far precluded its adoption Bayesian modelling. Using entropic reasoning we show that dropout can be interpreted optimal inference under constraints. We demonstrate this on an an...

Title of Thesis: SCHOOL DROPOUT AND SUBSEQUENT OFFENDING: DISTINGUISHING SELECTION FROM CAUSATION Gary Allen Sweeten, Master of Arts, 2004 Thesis directed by: Professor Shawn D. Bushway Department of Criminology and Criminal Justice Past research on the relationship between school dropout and offending is inconclusive. In explaining their findings, researchers have focused on strain and control...

Color dropout refers to the process of converting color form documents to black and white by removing the colors that are part of the blank form and maintaining only the information entered in the form. In this paper, no prior knowledge of the form type is assumed. Color dropout is performed by associating darker non-dropout colors with information that is entered in the form and needs to be pr...

Regularizing neural networks is an important task to reduce overfitting. Dropout [1] has been a widely-used regularization trick for neural networks. In convolutional neural networks (CNNs), dropout is usually applied to the fully connected layers. Meanwhile, the regularization effect of dropout in the convolutional layers has not been thoroughly analyzed in the literature. In this paper, we an...

We explore a recently proposed Variational Dropout technique that provided an elegant Bayesian interpretation to Gaussian Dropout. We extend Variational Dropout to the case when dropout rates are unbounded, propose a way to reduce the variance of the gradient estimator and report first experimental results with individual dropout rates per weight. Interestingly, it leads to extremely sparse sol...