Search Results for author: Jia Wu

Found 30 papers, 14 papers with code

DynSTGAT: Dynamic Spatial-Temporal Graph Attention Network for Traffic Signal Control

no code implementations12 Sep 2021 Libing Wu, Min Wang, Dan Wu, Jia Wu

Then, to efficiently utilize the historical state information of the intersection, we design a sequence model with the temporal convolutional network (TCN) to capture the historical information and further merge it with the spatial information to improve its performance.

Graph Attention

Event Extraction by Associating Event Types and Argument Roles

no code implementations23 Aug 2021 Qian Li, Shu Guo, Jia Wu, JianXin Li, Jiawei Sheng, Lihong Wang, Xiaohan Dong, Hao Peng

It ignores meaningful associations among event types and argument roles, leading to relatively poor performance for less frequent types/roles.

Document-level Event Extraction +2

Transferring Knowledge Distillation for Multilingual Social Event Detection

1 code implementation6 Aug 2021 Jiaqian Ren, Hao Peng, Lei Jiang, Jia Wu, Yongxin Tong, Lihong Wang, Xu Bai, Bo wang, Qiang Yang

Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce.

Event Detection Knowledge Distillation +1

A Comprehensive Survey on Schema-based Event Extraction with Deep Learning

no code implementations5 Jul 2021 Qian Li, Hao Peng, JianXin Li, Yiming Hei, Rui Sun, Jiawei Sheng, Shu Guo, Lihong Wang, Jia Wu, Amin Beheshti, Philip S. Yu

Numerous methods, datasets, and evaluation metrics have been proposed in the literature, raising the need for a comprehensive and updated survey.

Event Extraction

Hierarchical Phenotyping and Graph Modeling of Spatial Architecture in Lymphoid Neoplasms

1 code implementation30 Jun 2021 Pingjun Chen, Muhammad Aminu, Siba El Hussein, Joseph D. Khoury, Jia Wu

In the end, we built global graphs to abstract spatial interaction patterns and extract features for disease diagnosis.

A stochastic linearized proximal method of multipliers for convex stochastic optimization with expectation constraints

no code implementations22 Jun 2021 Liwei Zhang, Yule Zhang, Jia Wu, Xiantao Xiao

We present a computable stochastic approximation type algorithm, namely the stochastic linearized proximal method of multipliers, to solve this convex stochastic optimization problem.

Stochastic Optimization

A Comprehensive Survey on Graph Anomaly Detection with Deep Learning

1 code implementation14 Jun 2021 Xiaoxiao Ma, Jia Wu, Shan Xue, Jian Yang, Chuan Zhou, Quan Z. Sheng, Hui Xiong, Leman Akoglu

In this survey, we aim to provide a systematic and comprehensive review of the contemporary deep learning techniques for graph anomaly detection.

Anomaly Detection

dFDA-VeD: A Dynamic Future Demand Aware Vehicle Dispatching System

no code implementations10 Jun 2021 Yang Guo, Tarique Anwar, Jian Yang, Jia Wu

As the process should be socially and economically profitable, the task of vehicle dispatching is highly challenging, specially due to the time-varying travel demands and traffic conditions.

A Comprehensive Survey on Community Detection with Deep Learning

1 code implementation26 May 2021 Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu

A community reveals the features and connections of its members that are different from those in other communities in a network.

Community Detection Graph Attention +2

Task-adaptive Neural Process for User Cold-Start Recommendation

1 code implementation26 Feb 2021 Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao, Bin Wang

In this paper, we develop a novel meta-learning recommender called task-adaptive neural process (TaNP).

Meta-Learning Recommendation Systems

Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs

2 code implementations21 Jan 2021 Yuwei Cao, Hao Peng, Jia Wu, Yingtong Dou, JianXin Li, Philip S. Yu

The complexity and streaming nature of social messages make it appealing to address social event detection in an incremental learning setting, where acquiring, preserving, and extending knowledge are major concerns.

Event Detection Feature Engineering +3

A Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning

no code implementations3 Jan 2021 Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Dongxiao He, Jia Wu, Philip S. Yu, Weixiong Zhang

We conclude with discussions of the challenges of the field and suggestions of possible directions for future research.

Community Detection

Graph Stochastic Neural Networks for Semi-supervised Learning

1 code implementation NeurIPS 2020 Haibo Wang, Chuan Zhou, Xin Chen, Jia Wu, Shirui Pan, Jilong Wang

Graph Neural Networks (GNNs) have achieved remarkable performance in the task of the semi-supervised node classification.

Classification General Classification +2

Survey and Open Problems in Privacy Preserving Knowledge Graph: Merging, Query, Representation, Completion and Applications

no code implementations20 Nov 2020 Chaochao Chen, Jamie Cui, Guanfeng Liu, Jia Wu, Li Wang

In this paper, to fill this gap, we summarize the open problems for privacy preserving KG in data isolation setting and propose possible solutions for them.

Graph Geometry Interaction Learning

1 code implementation NeurIPS 2020 Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, Bin Wang

To utilize the strength of both Euclidean and hyperbolic geometries, we develop a novel Geometry Interaction Learning (GIL) method for graphs, a well-suited and efficient alternative for learning abundant geometric properties in graph.

Link Prediction Node Classification

A Deep Framework for Cross-Domain and Cross-System Recommendations

no code implementations14 Sep 2020 Feng Zhu, Yan Wang, Chaochao Chen, Guanfeng Liu, Mehmet Orgun, Jia Wu

Therefore, finding an accurate mapping of the latent factors across domains or systems is crucial to enhancing recommendation accuracy.

Recommendation Systems

Opinion Maximization in Social Trust Networks

1 code implementation19 Jun 2020 Pinghua Xu, Wenbin Hu, Jia Wu, Weiwei Liu

However, the practical significance of the existing studies on this subject is limited for two reasons.

Social and Information Networks Computer Science and Game Theory J.4

Heterogeneous Graph Attention Networks for Early Detection of Rumors on Twitter

1 code implementation10 Jun 2020 Qi Huang, Junshuai Yu, Jia Wu, Bin Wang

A meta-path based heterogeneous graph attention network framework is proposed to capture the global semantic relations of text contents, together with the global structure information of source tweet propagations for rumor detection.

Graph Attention

Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification

no code implementations25 May 2020 Jun Zhou, Chaochao Chen, Longfei Zheng, Huiwen Wu, Jia Wu, Xiaolin Zheng, Bingzhe Wu, Ziqi Liu, Li Wang

Recently, Graph Neural Network (GNN) has achieved remarkable progresses in various real-world tasks on graph data, consisting of node features and the adjacent information between different nodes.

Classification General Classification +1

Deep Learning for Community Detection: Progress, Challenges and Opportunities

1 code implementation17 May 2020 Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Jian Yang, Philip S. Yu

As communities represent similar opinions, similar functions, similar purposes, etc., community detection is an important and extremely useful tool in both scientific inquiry and data analytics.

Community Detection Graph Embedding

Deep Active Learning for Anchor User Prediction

1 code implementation18 Jun 2019 Anfeng Cheng, Chuan Zhou, Hong Yang, Jia Wu, Lei LI, Jianlong Tan, Li Guo

Due to the expensive costs of labeling anchor users for training prediction models, we consider in this paper the problem of minimizing the number of user pairs across multiple networks for labeling as to improve the accuracy of the prediction.

Active Learning

Deep segmentation networks predict survival of non-small cell lung cancer

1 code implementation26 Mar 2019 Stephen Baek, Yusen He, Bryan G. Allen, John M. Buatti, Brian J. Smith, Ling Tong, Zhiyu Sun, Jia Wu, Maximilian Diehn, Billy W. Loo, Kristin A. Plichta, Steven N. Seyedin, Maggie Gannon, Katherine R. Cabel, Yusung Kim, Xiaodong Wu

Here we show that CNN trained to perform the tumor segmentation task, with no other information than physician contours, identify a rich set of survival-related image features with remarkable prognostic value.

Tumor Segmentation

TLR: Transfer Latent Representation for Unsupervised Domain Adaptation

no code implementations19 Aug 2018 Pan Xiao, Bo Du, Jia Wu, Lefei Zhang, Ruimin Hu, Xuelong. Li

Many classic methods solve the domain adaptation problem by establishing a common latent space, which may cause the loss of many important properties across both domains.

Unsupervised Domain Adaptation

Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification

no code implementations14 Jan 2018 Chenglong Dai, Jia Wu, Dechang Pi, Lin Cui

Brain Electroencephalography (EEG) classification is widely applied to analyze cerebral diseases in recent years.

Classification EEG +2

Dynamic Island Model based on Spectral Clustering in Genetic Algorithm

no code implementations5 Jan 2018 Qinxue Meng, Jia Wu, John Ellisy, Paul J. Kennedy

One is that after a certain number of generations, different islands may retain quite similar, converged sub-populations thereby losing diversity and decreasing efficiency.

Subpopulation Diversity Based Selecting Migration Moment in Distributed Evolutionary Algorithms

no code implementations5 Jan 2017 Cheng-Jun Li, Jia Wu

In this paper, a scheme of setting the success rate of migration based on subpopulation diversity at each interval is proposed.

Traveling Salesman Problem

Temporal Feature Selection on Networked Time Series

no code implementations20 Dec 2016 Haishuai Wang, Jia Wu, Peng Zhang, Chengqi Zhang

For example, social network users are considered to be social sensors that continuously generate social signals (tweets) represented as a time series.

Feature Selection Time Series +2

PIGMIL: Positive Instance Detection via Graph Updating for Multiple Instance Learning

no code implementations12 Dec 2016 Dongkuan Xu, Jia Wu, Wei zhang, Yingjie Tian

To the end, we propose a positive instance detection via graph updating for multiple instance learning, called PIGMIL, to detect TPI accurately.

Multiple Instance Learning

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