338 citations · 610 across the 12 of their papers we have counts for
12 papers
Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network
Wenxuan Tu, Bin Xiao, Xinwang Liu +3
With the development of various applications, such as social networks and knowledge graphs, graph data has been ubiquitous in the real world. Unfortunately, graphs usually suffer f…
Partial Selfish Mining for More Profits
Jiaping Yu, Shang Gao, Rui Song +2
Mining attacks aim to gain an unfair share of extra rewards in the blockchain mining. Selfish mining can preserve discovered blocks and strategically release them, wasting honest m…
STEdge: Self-training Edge Detection with Multi-layer Teaching and Regularization
Yunfan Ye, Renjiao Yi, Zhiping Cai +1
Learning-based edge detection has hereunto been strongly supervised with pixel-wise annotations which are tedious to obtain manually. We study the problem of self-training edge det…
SmashEx: Smashing SGX Enclaves Using Exceptions
Jinhua Cui, Jason Zhijingcheng Yu, Shweta Shinde +2
Exceptions are a commodity hardware functionality which is central to multi-tasking OSes as well as event-driven user applications. Normally, the OS assists the user application by…
Video Abnormal Event Detection by Learning to Complete Visual Cloze Tests
Siqi Wang, Guang Yu, Zhiping Cai +3
Although deep neural networks (DNNs) enable great progress in video abnormal event detection (VAD), existing solutions typically suffer from two issues: (1) The localization of vid…
Deep Anomaly Discovery From Unlabeled Videos via Normality Advantage and Self-Paced Refinement
Guang Yu, Siqi Wang, Zhiping Cai +3
While classic video anomaly detection (VAD) requires labeled normal videos for training, emerging unsupervised VAD (UVAD) aims to discover anomalies directly from fully unlabeled v…
Deep Fusion Clustering Network
Wenxuan Tu, Sihang Zhou, Xinwang Liu +4
Deep clustering is a fundamental yet challenging task for data analysis. Recently we witness a strong tendency of combining autoencoder and graph neural networks to exploit structu…
Multi-View Spectral Clustering with High-Order Optimal Neighborhood Laplacian Matrix
Weixuan Liang, Sihang Zhou, Jian Xiong +5
Multi-view spectral clustering can effectively reveal the intrinsic cluster structure among data by performing clustering on the learned optimal embedding across views. Though demo…
Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events
Guang Yu, Siqi Wang, Zhiping Cai +4
As a vital topic in media content interpretation, video anomaly detection (VAD) has made fruitful progress via deep neural network (DNN). However, existing methods usually follow a…
A Survey on Edge Computing Systems and Tools
Fang Liu, Guoming Tang, Youhuizi Li +3
Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provi…
RepNet: Cutting Tail Latency in Data Center Networks with Flow Replication
Shuhao Liu, Wei Bai, Hong Xu +2
Data center networks need to provide low latency, especially at the tail, as demanded by many interactive applications. To improve tail latency, existing approaches require modific…
Low Latency Datacenter Networking: A Short Survey
Shuhao Liu, Hong Xu, Zhiping Cai
Datacenters are the cornerstone of the big data infrastructure supporting numerous online services. The demand for interactivity, which significantly impacts user experience and pr…