Search Results for author: Qi Xuan

Found 61 papers, 17 papers with code

Rethinking Graph Transformer Architecture Design for Node Classification

no code implementations15 Oct 2024 Jiajun Zhou, Xuanze Chen, Chenxuan Xie, Yu Shanqing, Qi Xuan, Xiaoniu Yang

Graph Transformer (GT), as a special type of Graph Neural Networks (GNNs), utilizes multi-head attention to facilitate high-order message passing.

Classification Computational Efficiency +1

Network Anomaly Traffic Detection via Multi-view Feature Fusion

no code implementations12 Sep 2024 Song Hao, Wentao Fu, Xuanze Chen, Chengxiang Jin, Jiajun Zhou, Shanqing Yu, Qi Xuan

MuFF models the temporal and interactive relationships of packets in network traffic based on the temporal and interactive viewpoints respectively.

Enhancing Ethereum Fraud Detection via Generative and Contrastive Self-supervision

no code implementations1 Aug 2024 Chenxiang Jin, Jiajun Zhou, Chenxuan Xie, Shanqing Yu, Qi Xuan, Xiaoniu Yang

The rampant fraudulent activities on Ethereum hinder the healthy development of the blockchain ecosystem, necessitating the reinforcement of regulations.

Fraud Detection

Dual-view Aware Smart Contract Vulnerability Detection for Ethereum

no code implementations29 Jun 2024 Jiacheng Yao, Maolin Wang, Wanqi Chen, Chengxiang Jin, Jiajun Zhou, Shanqing Yu, Qi Xuan

The wide application of Ethereum technology has brought technological innovation to traditional industries.

Vulnerability Detection

A Generic Layer Pruning Method for Signal Modulation Recognition Deep Learning Models

no code implementations12 Jun 2024 Yao Lu, Yutao Zhu, Yuqi Li, Dongwei Xu, Yun Lin, Qi Xuan, Xiaoniu Yang

With the successful application of deep learning in communications systems, deep neural networks are becoming the preferred method for signal classification.

Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property Prediction

1 code implementation24 May 2024 Zeyu Wang, Tianyi Jiang, Yao Lu, Xiaoze Bao, Shanqing Yu, Bin Wei, Qi Xuan

The knowledge-enhanced relation graph module constructs the molecule-property multi-relation graph (MPMRG) to capture the many-to-many relationships between molecules and properties.

Meta-Learning Molecular Property Prediction +3

Exploring the Impact of Dataset Bias on Dataset Distillation

1 code implementation24 Mar 2024 Yao Lu, Jianyang Gu, Xuguang Chen, Saeed Vahidian, Qi Xuan

Given that there are no suitable biased datasets for DD, we first construct two biased datasets, CMNIST-DD and CCIFAR10-DD, to establish a foundation for subsequent analysis.

Dataset Distillation

A Federated Parameter Aggregation Method for Node Classification Tasks with Different Graph Network Structures

no code implementations24 Mar 2024 Hao Song, Jiacheng Yao, Zhengxi Li, Shaocong Xu, Shibo Jin, Jiajun Zhou, Chenbo Fu, Qi Xuan, Shanqing Yu

Additionally, for the privacy security of FLGNN, this paper designs membership inference attack experiments and differential privacy defense experiments.

Federated Learning Graph Neural Network +3

Multi-Modal Representation Learning for Molecular Property Prediction: Sequence, Graph, Geometry

1 code implementation7 Jan 2024 Zeyu Wang, Tianyi Jiang, Jinhuan Wang, Qi Xuan

Molecular property prediction refers to the task of labeling molecules with some biochemical properties, playing a pivotal role in the drug discovery and design process.

Data Augmentation Drug Discovery +4

Deep Learning-Based Frequency Offset Estimation

no code implementations8 Nov 2023 Tao Chen, Shilian Zheng, Jiawei Zhu, Qi Xuan, Xiaoniu Yang

In wireless communication systems, the asynchronization of the oscillators in the transmitter and the receiver along with the Doppler shift due to relative movement may lead to the presence of carrier frequency offset (CFO) in the received signals.

Deep Learning

RK-core: An Established Methodology for Exploring the Hierarchical Structure within Datasets

1 code implementation10 Oct 2023 Yao Lu, Yutian Huang, Jiaqi Nie, Zuohui Chen, Qi Xuan

Across several benchmark datasets, we find that samples with low coreness values appear less representative of their respective categories, and conversely, those with high coreness values exhibit greater representativeness.

Diversity

Can pre-trained models assist in dataset distillation?

1 code implementation5 Oct 2023 Yao Lu, Xuguang Chen, Yuchen Zhang, Jianyang Gu, Tianle Zhang, Yifan Zhang, Xiaoniu Yang, Qi Xuan, Kai Wang, Yang You

Dataset Distillation (DD) is a prominent technique that encapsulates knowledge from a large-scale original dataset into a small synthetic dataset for efficient training.

Dataset Distillation Diversity

PathMLP: Smooth Path Towards High-order Homophily

1 code implementation23 Jun 2023 Jiajun Zhou, Chenxuan Xie, Shengbo Gong, Jiaxu Qian, Shanqing Yu, Qi Xuan, Xiaoniu Yang

However, common practices in GNNs to acquire high-order information mainly through increasing model depth and altering message-passing mechanisms, which, albeit effective to a certain extent, suffer from three shortcomings: 1) over-smoothing due to excessive model depth and propagation times; 2) high-order information is not fully utilized; 3) low computational efficiency.

Computational Efficiency Representation Learning

Subgraph Networks Based Contrastive Learning

no code implementations6 Jun 2023 Jinhuan Wang, Jiafei Shao, Zeyu Wang, Shanqing Yu, Qi Xuan, Xiaoniu Yang

In addition, we also investigate the impact of the second-order subgraph augmentation on mining graph structure interactions, and further, propose a contrastive objective that fuses the first-order and second-order subgraph information.

Attribute Contrastive Learning +3

Clarify Confused Nodes via Separated Learning

no code implementations4 Jun 2023 Jiajun Zhou, Shengbo Gong, Xuanze Chen, Chenxuan Xie, Shanqing Yu, Qi Xuan, Xiaoniu Yang

A minority of studies attempt to train different node groups separately but suffer from inappropriate separation metrics and low efficiency.

Node Classification

How does Contrastive Learning Organize Images?

1 code implementation17 May 2023 Yunzhe Zhang, Yao Lu, Qi Xuan

Contrastive learning, a dominant self-supervised technique, emphasizes similarity in representations between augmentations of the same input and dissimilarity for different ones.

Clustering Contrastive Learning

Single Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning

no code implementations4 May 2023 Dayuan Chen, Jian Zhang, Yuqian Lv, Jinhuan Wang, Hongjie Ni, Shanqing Yu, Zhen Wang, Qi Xuan

Furthermore, most methods concentrate on a single attack goal and lack a generalizable adversary to develop distinct attack strategies for diverse goals, thus limiting precise control over victim model behavior in real-world scenarios.

Specificity

SR-init: An interpretable layer pruning method

1 code implementation14 Mar 2023 Hui Tang, Yao Lu, Qi Xuan

Our SR-init method is inspired by the discovery that the accuracy drop due to stochastic re-initialization of layer parameters differs in various layers.

Neighborhood Homophily-based Graph Convolutional Network

1 code implementation24 Jan 2023 Shengbo Gong, Jiajun Zhou, Chenxuan Xie, Qi Xuan

Graph neural networks (GNNs) have been proved powerful in graph-oriented tasks.

Node Classification

Data Augmentation on Graphs: A Technical Survey

1 code implementation20 Dec 2022 Jiajun Zhou, Chenxuan Xie, Shengbo Gong, Zhenyu Wen, Xiangyu Zhao, Qi Xuan, Xiaoniu Yang

To advance research in this emerging direction, this survey provides a comprehensive review and summary of existing graph data augmentation (GDAug) techniques.

Data Augmentation Graph Representation Learning +1

Discover Important Paths in the Knowledge Graph Based on Dynamic Relation Confidence

no code implementations2 Nov 2022 Shanqing Yu, Yijun Wu, Ran Gan, Jiajun Zhou, Ziwan Zheng, Qi Xuan

Most of the existing knowledge graphs are not usually complete and can be complemented by some reasoning algorithms.

Knowledge Graphs Relation

Time-aware Metapath Feature Augmentation for Ponzi Detection in Ethereum

no code implementations30 Oct 2022 Chengxiang Jin, Jiajun Zhou, Jie Jin, Jiajing Wu, Qi Xuan

With the development of Web 3. 0 which emphasizes decentralization, blockchain technology ushers in its revolution and also brings numerous challenges, particularly in the field of cryptocurrency.

GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections

1 code implementation23 Oct 2022 Junyuan Fang, Haixian Wen, Jiajing Wu, Qi Xuan, Zibin Zheng, Chi K. Tse

Specifically, to make the node injections as imperceptible and effective as possible, we propose a sampling operation to determine the degree of the newly injected nodes, and then generate features and select neighbors for these injected nodes based on the statistical information of features and evolutionary perturbations obtained from a genetic algorithm, respectively.

SubGraph Networks based Entity Alignment for Cross-lingual Knowledge Graph

no code implementations7 May 2022 Shanqing Yu, Shihan Zhang, Jianlin Zhang, Jiajun Zhou, Qi Xuan, Bing Li, Xiaojuan Hu

Cross-lingual knowledge graph entity alignment aims to discover the cross-lingual links in the multi-language KGs, which is of great significance to the NLP applications and multi-language KGs fusion.

Entity Alignment Knowledge Graphs

Cross Cryptocurrency Relationship Mining for Bitcoin Price Prediction

no code implementations28 Apr 2022 Panpan Li, Shengbo Gong, Shaocong Xu, Jiajun Zhou, Yu Shanqing, Qi Xuan

In this work, we propose a generic Cross-Cryptocurrency Relationship Mining module, named C2RM, which can effectively capture the synchronous and asynchronous impact factors between Bitcoin and related Altcoins.

Dynamic Time Warping

Improving robustness of language models from a geometry-aware perspective

no code implementations Findings (ACL) 2022 Bin Zhu, Zhaoquan Gu, Le Wang, Jinyin Chen, Qi Xuan

On top of FADA, we propose geometry-aware adversarial training (GAT) to perform adversarial training on friendly adversarial data so that we can save a large number of search steps.

Data Augmentation

Mixing Signals: Data Augmentation Approach for Deep Learning Based Modulation Recognition

no code implementations5 Apr 2022 Xinjie Xu, Zhuangzhi Chen, Dongwei Xu, Huaji Zhou, Shanqing Yu, Shilian Zheng, Qi Xuan, Xiaoniu Yang

Data augmentation, as the strategy of expanding dataset, can improve the generalization of the deep learning models and thus improve the accuracy of the models to a certain extent.

Automatic Modulation Recognition Classification +2

Hyperspectral Imaging for cherry tomato

no code implementations10 Mar 2022 Yun Xiang, Qijun Chen, Zhongjin Su, Lu Zhang, Zuohui Chen, Guozhi Zhou, Zhuping Yao, Qi Xuan, Yuan Cheng

Cherry tomato (Solanum Lycopersicum) is popular with consumers over the world due to its special flavor.

regression

A Multi-View Framework for BGP Anomaly Detection via Graph Attention Network

no code implementations23 Dec 2021 Songtao Peng, Jiaqi Nie, Xincheng Shu, Zhongyuan Ruan, Lei Wang, Yunxuan Sheng, Qi Xuan

As the default protocol for exchanging routing reachability information on the Internet, the abnormal behavior in traffic of Border Gateway Protocols (BGP) is closely related to Internet anomaly events.

Anomaly Detection feature selection +3

Understanding the Dynamics of DNNs Using Graph Modularity

1 code implementation24 Nov 2021 Yao Lu, Wen Yang, Yunzhe Zhang, Zuohui Chen, Jinyin Chen, Qi Xuan, Zhen Wang, Xiaoniu Yang

Specifically, we model the process of class separation of intermediate representations in pre-trained DNNs as the evolution of communities in dynamic graphs.

Feature Engineering

Graph-Based Similarity of Neural Network Representations

1 code implementation22 Nov 2021 Zuohui Chen, Yao Lu, Jinxuan Hu, Wen Yang, Qi Xuan, Zhen Wang, Xiaoniu Yang

Understanding the black-box representations in Deep Neural Networks (DNN) is an essential problem in deep learning.

RGP: Neural Network Pruning through Its Regular Graph Structure

no code implementations28 Oct 2021 Zhuangzhi Chen, Jingyang Xiang, Yao Lu, Qi Xuan, Xiaoniu Yang

In this paper, we study the graph structure of the neural network, and propose regular graph based pruning (RGP) to perform a one-shot neural network pruning.

Network Pruning

Deep Transfer Clustering of Radio Signals

no code implementations26 Jul 2021 Qi Xuan, Xiaohui Li, Zhuangzhi Chen, Dongwei Xu, Shilian Zheng, Xiaoniu Yang

In this letter, we turn to the more challenging problem: can we cluster the modulation types just based on a large number of unlabeled radio signals?

Clustering Deep Clustering +1

GGT: Graph-Guided Testing for Adversarial Sample Detection of Deep Neural Network

no code implementations9 Jul 2021 Zuohui Chen, Renxuan Wang, Jingyang Xiang, Yue Yu, Xin Xia, Shouling Ji, Qi Xuan, Xiaoniu Yang

Deep Neural Networks (DNN) are known to be vulnerable to adversarial samples, the detection of which is crucial for the wide application of these DNN models.

Diversity

Adversarial Sample Detection via Channel Pruning

no code implementations ICML Workshop AML 2021 Zuohui Chen, Renxuan Wang, Yao Lu, Jingyang Xiang, Qi Xuan

Experiments on CIFAR10 and SVHN show that the FLOPs and size of our generated model are only 24. 46\% and 4. 86\% of the original model.

Adaptive Visibility Graph Neural Network and It's Application in Modulation Classification

no code implementations16 Jun 2021 Qi Xuan, Kunfeng Qiu, Jinchao Zhou, Zhuangzhi Chen, Dongwei Xu, Shilian Zheng, Xiaoniu Yang

In this paper, we propose an Adaptive Visibility Graph (AVG) algorithm that can adaptively map time series into graphs, based on which we further establish an end-to-end classification framework AVGNet, by utilizing GNN model DiffPool as the classifier.

Avg Graph Neural Network +2

TSGN: Transaction Subgraph Networks for Identifying Ethereum Phishing Accounts

no code implementations18 Apr 2021 Jinhuan Wang, Pengtao Chen, Shanqing Yu, Qi Xuan

In this paper, we propose a Transaction SubGraph Network (TSGN) based classification model to identify phishing accounts in Ethereum.

Graph Representation Learning

Identity Inference on Blockchain using Graph Neural Network

1 code implementation14 Apr 2021 Jie Shen, Jiajun Zhou, Yunyi Xie, Shanqing Yu, Qi Xuan

In this paper, we present a novel approach to analyze user's behavior from the perspective of the transaction subgraph, which naturally transforms the identity inference task into a graph classification pattern and effectively avoids computation in large-scale graph.

Graph Classification Graph Mining +1

CLPVG: Circular limited penetrable visibility graph as a new network model for time series

no code implementations1 Mar 2021 Qi Xuan, Jinchao Zhou, Kunfeng Qiu, Dongwei Xu, Shilian Zheng, Xiaoniu Yang

Visibility Graph (VG) transforms time series into graphs, facilitating signal processing by advanced graph data mining algorithms.

Clustering EEG +4

HVAQ: A High-Resolution Vision-Based Air Quality Dataset

1 code implementation18 Feb 2021 Zuohui Chen, Tony Zhang, Zhuangzhi Chen, Yun Xiang, Qi Xuan, Robert P. Dick

The main contribution of this paper is that to the best of our knowledge, it is the first publicly available, high temporal and spatial resolution air quality dataset containing simultaneous point sensor measurements and corresponding images.

Vocal Bursts Intensity Prediction

Temporal-Amount Snapshot MultiGraph for Ethereum Transaction Tracking

no code implementations16 Feb 2021 Yunyi Xie, Jie Jin, Jian Zhang, Shanqing Yu, Qi Xuan

With the wide application of blockchain in the financial field, the rise of various types of cybercrimes has brought great challenges to the security of blockchain.

Link Prediction

MITNet: GAN Enhanced Magnetic Induction Tomography Based on Complex CNN

no code implementations16 Feb 2021 Zuohui Chen, Qing Yuan, Xujie Song, Cheng Chen, Dan Zhang, Yun Xiang, Ruigang Liu, Qi Xuan

Magnetic induction tomography (MIT) is an efficient solution for long-term brain disease monitoring, which focuses on reconstructing bio-impedance distribution inside the human brain using non-intrusive electromagnetic fields.

Generative Adversarial Network Image Reconstruction

Time-Series Snapshot Network for Partner Recommendation: A Case Study on OSS

no code implementations18 Nov 2020 Jinyin Chen, Yunyi Xie, Jian Zhang, Xincheng Shu, Qi Xuan

In this paper, we introduce time-series snapshot network (TSSN) which is a mixture network to model the interactions among users and developers.

Social and Information Networks

SigNet: A Novel Deep Learning Framework for Radio Signal Classification

no code implementations28 Oct 2020 Zhuangzhi Chen, Hui Cui, Jingyang Xiang, Kunfeng Qiu, Liang Huang, Shilian Zheng, Shichuan Chen, Qi Xuan, Xiaoniu Yang

More interestingly, our proposed models behave extremely well in small-sample learning when only a small training dataset is provided.

Classification Deep Learning +2

M-Evolve: Structural-Mapping-Based Data Augmentation for Graph Classification

no code implementations11 Jul 2020 Jiajun Zhou, Jie Shen, Shanqing Yu, Guanrong Chen, Qi Xuan

Graph classification, which aims to identify the category labels of graphs, plays a significant role in drug classification, toxicity detection, protein analysis etc.

Data Augmentation General Classification +1

MGA: Momentum Gradient Attack on Network

no code implementations26 Feb 2020 Jinyin Chen, Yixian Chen, Haibin Zheng, Shijing Shen, Shanqing Yu, Dan Zhang, Qi Xuan

The adversarial attack methods based on gradient information can adequately find the perturbations, that is, the combinations of rewired links, thereby reducing the effectiveness of the deep learning model based graph embedding algorithms, but it is also easy to fall into a local optimum.

Social and Information Networks

Adversarial Attacks to Scale-Free Networks: Testing the Robustness of Physical Criteria

no code implementations4 Feb 2020 Qi Xuan, Yalu Shan, Jinhuan Wang, Zhongyuan Ruan, Guanrong Chen

It is found that both DALR and DILR are more effective than RLR, in the sense that rewiring a smaller number of links can succeed in the same attack.

Social and Information Networks Physics and Society

Time-aware Gradient Attack on Dynamic Network Link Prediction

no code implementations24 Nov 2019 Jinyin Chen, Jian Zhang, Zhi Chen, Min Du, Qi Xuan

In this work, we present the first study of adversarial attack on dynamic network link prediction (DNLP).

Adversarial Attack Link Prediction +1

Multiscale Evolutionary Perturbation Attack on Community Detection

no code implementations22 Oct 2019 Jinyin Chen, Yixian Chen, Lihong Chen, Minghao Zhao, Qi Xuan

In this paper, we formalize this community detection attack problem in three scales, including global attack (macroscale), target community attack (mesoscale) and target node attack (microscale).

Social and Information Networks Physics and Society

Open DNN Box by Power Side-Channel Attack

no code implementations21 Jul 2019 Yun Xiang, Zhuangzhi Chen, Zuohui Chen, Zebin Fang, Haiyang Hao, Jinyin Chen, Yi Liu, Zhefu Wu, Qi Xuan, Xiaoniu Yang

However, recent studies indicate that they are also vulnerable to adversarial attacks.

MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks

no code implementations15 Jun 2019 Qi Xuan, Fuxian Li, Yi Liu, Yun Xiang

Experimental results on ModelNet10 and ModelNet40 datasets show that our MV-C3D technique can achieve outstanding performance with multi-view images which are captured from partial angles with less range.

3D Object Recognition

Unsupervised Euclidean Distance Attack on Network Embedding

no code implementations27 May 2019 Qi Xuan, Jun Zheng, Lihong Chen, Shanqing Yu, Jinyin Chen, Dan Zhang, Qingpeng Zhang Member

Since a large number of downstream network algorithms, such as community detection and node classification, rely on the Euclidean distance between nodes to evaluate the similarity between them in the embedding space, EDA can be considered as a universal attack on a variety of network algorithms.

Social and Information Networks Physics and Society

N2VSCDNNR: A Local Recommender System Based on Node2vec and Rich Information Network

no code implementations12 Apr 2019 Jinyin Chen, Yangyang Wu, Lu Fan, Xiang Lin, Haibin Zheng, Shanqing Yu, Qi Xuan

In particular, we use a bipartite network to construct the user-item network, and represent the interactions among users (or items) by the corresponding one-mode projection network.

Clustering Recommendation Systems

Subgraph Networks with Application to Structural Feature Space Expansion

no code implementations21 Mar 2019 Qi Xuan, Jinhuan Wang, Minghao Zhao, Junkun Yuan, Chenbo Fu, Zhongyuan Ruan, Guanrong Chen

In other words, the structural features of SGNs can complement that of the original network for better network classification, regardless of the feature extraction method used, such as the handcrafted, network embedding and kernel-based methods.

General Classification Graph Classification +1

Can Adversarial Network Attack be Defended?

no code implementations11 Mar 2019 Jinyin Chen, Yangyang Wu, Xiang Lin, Qi Xuan

In this paper, we are interested in the possibility of defense against adversarial attack on network, and propose defense strategies for GNNs against attacks.

Social and Information Networks Physics and Society

E-LSTM-D: A Deep Learning Framework for Dynamic Network Link Prediction

1 code implementation22 Feb 2019 Jinyin Chen, Jian Zhang, Xuanheng Xu, Chengbo Fu, Dan Zhang, Qingpeng Zhang, Qi Xuan

Predicting the potential relations between nodes in networks, known as link prediction, has long been a challenge in network science.

Decoder Link Prediction +1

GA Based Q-Attack on Community Detection

no code implementations1 Nov 2018 Jinyin Chen, Lihong Chen, Yixian Chen, Minghao Zhao, Shanqing Yu, Qi Xuan, Xiaoniu Yang

In particular, we first give two heuristic attack strategies, i. e., Community Detection Attack (CDA) and Degree Based Attack (DBA), as baselines, utilizing the information of detected community structure and node degree, respectively.

Social and Information Networks

Target Defense Against Link-Prediction-Based Attacks via Evolutionary Perturbations

no code implementations16 Sep 2018 Shanqing Yu, Minghao Zhao, Chenbo Fu, Huimin Huang, Xincheng Shu, Qi Xuan, Guanrong Chen

This is the first time to study privacy protection on targeted links against link-prediction-based attacks.

Social and Information Networks Physics and Society

Fast Gradient Attack on Network Embedding

no code implementations8 Sep 2018 Jinyin Chen, Yangyang Wu, Xuanheng Xu, Yixian Chen, Haibin Zheng, Qi Xuan

Network embedding maps a network into a low-dimensional Euclidean space, and thus facilitate many network analysis tasks, such as node classification, link prediction and community detection etc, by utilizing machine learning methods.

Physics and Society Social and Information Networks

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