48 citations · 152 across the 18 of their papers we have counts for
18 papers
From MIM-Based GAN to Anomaly Detection:Event Probability Influence on Generative Adversarial Networks
Rui She, Pingyi Fan
In order to introduce deep learning technologies into anomaly detection, Generative Adversarial Networks (GANs) are considered as important roles in the algorithm design and realis…
Location-Adaptive Change-Point Testing for Time Series
Linlin Dai, Rui She
We propose a location-adaptive self-normalization (SN) based test for change points in time series. The SN technique has been extensively used in change-point detection for its cap…
An Importance Aware Weighted Coding Theorem Using Message Importance Measure
Zheqi Zhu, Shanyun Liu, Rui She +3
There are numerous scenarios in source coding where not only the code length but the importance of each value should also be taken into account. Different from the traditional codi…
MIM-Based GAN: Information Metric to Amplify Small Probability Events Importance in Generative Adversarial Networks
Rui She, Pingyi Fan
In terms of Generative Adversarial Networks (GANs), the information metric to discriminate the generative data from the real data, lies in the key point of generation efficiency, w…
Storage Space Allocation Strategy for Digital Data with Message Importance
Shanyun Liu, Rui She, Zheqi Zhu +1
This paper mainly focuses on the problem of lossy compression storage from the perspective of message importance when the reconstructed data pursues the least distortion within lim…
Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges
Rui She, Shanyun Liu, Shuo Wan +2
In many applications (e.g., anomaly detection and security systems) of smart cities, rare events dominate the importance of the total information of big data collected by Internet…