Zheng Yan

TL;DR: A redundancy removing aggregation network (RRAN) for video face recognition that can diminish the overall influence of poor quality components with large proportion in the video and further improve the overall recognition performance with individual difference is proposed.

TL;DR: In this paper, the authors proposed a new model based on expected utility theory (EUT) and employed a hybrid genetic algorithm (GA) and Monte-Carlo simulation technique as solution approach to deal with the trading portfolios whose return distribution is non-normal.

TL;DR: In this paper, a combined architecture comprising a Conditional Variational AutoEncoder (CVAE) and a Random Forest (RF) classifier is proposed to automatically learn similarity among input features, provide data distribution in order to extract discriminative features from original features, and finally classify various types of attacks.

TL;DR: In this article , the authors applied multiple unsupervised algorithms and a co-association matrix to detect attack clusters of any shape as long as they have density-connected elements.

TL;DR: In this article, an example apparatus is provided that includes a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to at least perform a number of operations.