204 citations · 604 across the 31 of their papers we have counts for
31 papers
Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting
Qiming Wu, Zhikang Zou, Pan Zhou +3
Crowd counting has drawn much attention due to its importance in safety-critical surveillance systems. Especially, deep neural network (DNN) methods have significantly reduced esti…
V3H: View Variation and View Heredity for Incomplete Multi-view Clustering
Xiang Fang, Yuchong Hu, Pan Zhou +1
Real data often appear in the form of multiple incomplete views. Incomplete multi-view clustering is an effective method to integrate these incomplete views. Previous methods only…
ANIMC: A Soft Framework for Auto-weighted Noisy and Incomplete Multi-view Clustering
Xiang Fang, Yuchong Hu, Pan Zhou +1
Multi-view clustering has wide applications in many image processing scenarios. In these scenarios, original image data often contain missing instances and noises, which is ignored…
Unbalanced Incomplete Multi-view Clustering via the Scheme of View Evolution: Weak Views are Meat; Strong Views do Eat
Xiang Fang, Yuchong Hu, Pan Zhou +1
Incomplete multi-view clustering is an important technique to deal with real-world incomplete multi-view data. Previous works assume that all views have the same incompleteness, i.…
Communication-efficient Decentralized Machine Learning over Heterogeneous Networks
Pan Zhou, Qian Lin, Dumitrel Loghin +3
In the last few years, distributed machine learning has been usually executed over heterogeneous networks such as a local area network within a multi-tenant cluster or a wide area…
Reinforcement Learning-based Black-Box Evasion Attacks to Link Prediction in Dynamic Graphs
Houxiang Fan, Binghui Wang, Pan Zhou +6
Link prediction in dynamic graphs (LPDG) is an important research problem that has diverse applications such as online recommendations, studies on disease contagion, organizational…
Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function
Binghui Wang, Tianxiang Zhou, Minhua Lin +5
Graph neural network (GNN), the mainstream method to learn on graph data, is vulnerable to graph evasion attacks, where an attacker slightly perturbing the graph structure can fool…
Jointly Cross- and Self-Modal Graph Attention Network for Query-Based Moment Localization
Daizong Liu, Xiaoye Qu, Xiao-Yang Liu +3
Query-based moment localization is a new task that localizes the best matched segment in an untrimmed video according to a given sentence query. In this localization task, one shou…
Identity-Aware Attribute Recognition via Real-Time Distributed Inference in Mobile Edge Clouds
Zichuan Xu, Jiangkai Wu, Qiufen Xia +3
With the development of deep learning technologies, attribute recognition and person re-identification (re-ID) have attracted extensive attention and achieved continuous improvemen…
Fine-grained Iterative Attention Network for TemporalLanguage Localization in Videos
Xiaoye Qu, Pengwei Tang, Zhikang Zhou +3
Temporal language localization in videos aims to ground one video segment in an untrimmed video based on a given sentence query. To tackle this task, designing an effective model t…
AN-GCN: An Anonymous Graph Convolutional Network Defense Against Edge-Perturbing Attack
Ao Liu, Beibei Li, Tao Li +2
Recent studies have revealed the vulnerability of graph convolutional networks (GCNs) to edge-perturbing attacks, such as maliciously inserting or deleting graph edges. However, a…
Cost-efficient and Skew-aware Data Scheduling for Incremental Learning in 5G Network
Lingjun Pu, Xinjing Yuan, Xiaohang Xu +3
To facilitate the emerging applications in 5G networks, mobile network operators will provide many network functions in terms of control and prediction. Recently, they have recogni…
Position-Aware Self-Attention based Neural Sequence Labeling
Wei Wei, Zanbo Wang, Xianling Mao +3
Sequence labeling is a fundamental task in natural language processing and has been widely studied. Recently, RNN-based sequence labeling models have increasingly gained attentions…
Joint Coverage and Power Control in Highly Dynamic and Massive UAV Networks: An Aggregative Game-theoretic Learning Approach
Zhuoying Li, Pan Zhou, Yanru Zhang +1
Unmanned aerial vehicles (UAV) ad-hoc network is a significant contingency plan for communication after a natural disaster, such as typhoon and earthquake. To achieve efficient and…
EnlightenGAN: Deep Light Enhancement without Paired Supervision
Yifan Jiang, Xinyu Gong, Ding Liu +6
Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data? As o…
MHP-VOS: Multiple Hypotheses Propagation for Video Object Segmentation
Shuangjie Xu, Daizong Liu, Linchao Bao +2
We address the problem of semi-supervised video object segmentation (VOS), where the masks of objects of interests are given in the first frame of an input video. To deal with chal…
Spatio-temporal Edge Service Placement: A Bandit Learning Approach
Lixing Chen, Jie Xu, Shaolei Ren +1
Shared edge computing platforms deployed at the radio access network are expected to significantly improve quality of service delivered by Application Service Providers (ASPs) in a…
Adaptive Fog Configuration for the Industrial Internet of Things
Lixing Chen, Pan Zhou, Liang Gao +1
Industrial Fog computing deploys various industrial services, such as automatic monitoring/control and imminent failure detection, at the Fog Nodes (FNs) to improve the performance…
Joint Service Caching and Task Offloading for Mobile Edge Computing in Dense Networks
Jie Xu, Lixing Chen, Pan Zhou
Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized cloud to the network edge, thereby meeting the latency requirements of many emerging mobile a…
Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification
Shuangjie Xu, Yu Cheng, Kang Gu +3
Person Re-Identification (person re-id) is a crucial task as its applications in visual surveillance and human-computer interaction. In this work, we present a novel joint Spatial…
Optimal Repair Layering for Erasure-Coded Data Centers: From Theory to Practice
Yuchong Hu, Xiaolu Li, Mi Zhang +4
Repair performance in hierarchical data centers is often bottlenecked by cross-rack network transfer. Recent theoretical results show that the cross-rack repair traffic can be mini…
Context-Aware Online Learning for Course Recommendation of MOOC Big Data
Yifan Hou, Pan Zhou, Ting Wang +3
The Massive Open Online Course (MOOC) has expanded significantly in recent years. With the widespread of MOOC, the opportunity to study the fascinating courses for free has attract…
Near Optimal Adaptive Shortest Path Routing with Stochastic Links States under Adversarial Attack
Pan Zhou, Lin Cheng, Dapeng Oliver Wu
We consider the shortest path routing (SPR) of a network with stochastically time varying link metrics under potential adversarial attacks. Due to potential denial of service attac…
Private and Truthful Aggregative Game for Large-Scale Spectrum Sharing
Pan Zhou, Wenqi Wei, Kaigui Bian +3
Thanks to the rapid development of information technology, the size of the wireless network becomes larger and larger, which makes spectrum resources more precious than ever before…