Search Results for author: Yixian Chen

Found 7 papers, 1 papers with code

Scalable Low-Rank Tensor Learning for Spatiotemporal Traffic Data Imputation

2 code implementations7 Aug 2020 Xinyu Chen, Yixian Chen, Nicolas Saunier, Lijun Sun

Recent studies based on tensor nuclear norm have demonstrated the superiority of tensor learning in imputation tasks by effectively characterizing the complex correlations/dependencies in spatiotemporal data.

Imputation Traffic Data Imputation

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

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

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

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

Probabilistic Outlier Detection and Generation

no code implementations22 Dec 2020 Stefano Giovanni Rizzo, Linsey Pang, Yixian Chen, Sanjay Chawla

A new method for outlier detection and generation is introduced by lifting data into the space of probability distributions which are not analytically expressible, but from which samples can be drawn using a neural generator.

Outlier Detection

Potential destination discovery for low predictability individuals based on knowledge graph

no code implementations30 Jan 2022 Guilong Li, Yixian Chen, Qionghua Liao, Zhaocheng He

We first construct a trip knowledge graph (TKG) to model the trip scenario by entities (e. g., travelers, destinations and time information) and their relationships, in which we introduce the concept of private relationship for complexity reduction.

Knowledge Graph Embedding

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