Chuxu Zhang

According to our database, Chuxu Zhang authored at least 109 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Safety in Graph Machine Learning: Threats and Safeguards.

Song Wang, Yushun Dong, Binchi Zhang, Zihan Chen, Xingbo Fu, Yinhan He, Cong Shen, Chuxu Zhang, Nitesh V. Chawla, Jundong Li

CoRR, 2024

Graph Inference Acceleration by Learning MLPs on Graphs without Supervision.

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

CoRR, 2024

Tackling Negative Transfer on Graphs.

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

CoRR, 2024

UGMAE: A Unified Framework for Graph Masked Autoencoders.

Yijun Tian, Chuxu Zhang, Ziyi Kou, Zheyuan Liu, Xiangliang Zhang, Nitesh V. Chawla

CoRR, 2024

Dual-level Hypergraph Contrastive Learning with Adaptive Temperature Enhancement.

Yiyue Qian, Tianyi Ma, Chuxu Zhang, Yanfang Ye

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

Symbolic Prompt Tuning Completes the App Promotion Graph.

Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Shang Ma, Chaoran Chen, Toby Li, Xusheng Xiao, Chuxu Zhang, Yanfang Ye

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery.

Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns.

Zheyuan Zhang, Zehong Wang, Shifu Hou, Evan Hall, Landon Bachman, Jasmine White, Vincent Galassi, Nitesh V. Chawla, Chuxu Zhang, Yanfang Ye

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Graph Cross Supervised Learning via Generalized Knowledge.

Xiangchi Yuan, Yijun Tian, Chunhui Zhang, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Subgraph Pooling: Tackling Negative Transfer on Graphs.

Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

How to Improve Representation Alignment and Uniformity in Graph-Based Collaborative Filtering?

Zhongyu Ouyang, Chunhui Zhang, Shifu Hou, Chuxu Zhang, Yanfang Ye

Proceedings of the Eighteenth International AAAI Conference on Web and Social Media, 2024

From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble.

Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, Yanfang Ye

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mitigating Emergent Robustness Degradation while Scaling Graph Learning.

Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning.

Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang

Trans. Mach. Learn. Res., 2023

Knowledge Distillation on Graphs: A Survey.

Yijun Tian, Shichao Pei, Xiangliang Zhang, Chuxu Zhang, Nitesh V. Chawla

CoRR, 2023

Multi-Modal Self-Supervised Learning for Recommendation.

Wei Wei, Chao Huang, Lianghao Xia, Chuxu Zhang

Proceedings of the ACM Web Conference 2023, 2023

Fair Graph Representation Learning via Diverse Mixture-of-Experts.

Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang

Proceedings of the ACM Web Conference 2023, 2023

Interpretable Research Interest Shift Detection with Temporal Heterogeneous Graphs.

Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Self-Supervised Graph Structure Refinement for Graph Neural Networks.

Jianan Zhao, Qianlong Wen, Mingxuan Ju, Chuxu Zhang, Yanfang Ye

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery.

Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Counterfactual Learning on Heterogeneous Graphs with Greedy Perturbation.

Qiang Yang, Changsheng Ma, Qiannan Zhang, Xin Gao, Chuxu Zhang, Xiangliang Zhang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Graph-based Molecular Representation Learning.

Zhichun Guo, Kehan Guo, Bozhao Nan, Yijun Tian, Roshni G. Iyer, Yihong Ma, Olaf Wiest, Xiangliang Zhang, Wei Wang, Chuxu Zhang, Nitesh V. Chawla

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations.

Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang

Proceedings of the International Conference on Machine Learning, 2023

Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization.

Chunhui Zhang, Yijun Tian, Mingxuan Ju, Zheyuan Liu, Yanfang Ye, Nitesh V. Chawla, Chuxu Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization.

Mingxuan Ju, Tong Zhao, Qianlong Wen, Wenhao Yu, Neil Shah, Yanfang Ye, Chuxu Zhang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency.

Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Hypergraph Contrastive Learning for Drug Trafficking Community Detection.

Tianyi Ma, Yiyue Qian, Chuxu Zhang, Yanfang Ye

Proceedings of the IEEE International Conference on Data Mining, 2023

A Multi-Modality Framework for Drug-Drug Interaction Prediction by Harnessing Multi-source Data.

Qianlong Wen, Jiazheng Li, Chuxu Zhang, Yanfang Ye

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Heterogeneous Temporal Graph Neural Network Explainer.

Jiazheng Li, Chunhui Zhang, Chuxu Zhang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Cross-Domain Few-Shot Graph Classification with a Reinforced Task Coordinator.

Qiannan Zhang, Shichao Pei, Qiang Yang, Chuxu Zhang, Nitesh V. Chawla, Xiangliang Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Towards Societal Impact of AI.

Chuxu Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Let Graph Be the Go Board: Gradient-Free Node Injection Attack for Graph Neural Networks via Reinforcement Learning.

Mingxuan Ju, Yujie Fan, Chuxu Zhang, Yanfang Ye

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Boosting Graph Neural Networks via Adaptive Knowledge Distillation.

Zhichun Guo, Chunhui Zhang, Yujie Fan, Yijun Tian, Chuxu Zhang, Nitesh V. Chawla

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Heterogeneous Graph Masked Autoencoders.

Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Grounded Task Prioritization with Context-Aware Sequential Ranking.

Chuxu Zhang, Julia Kiseleva, Sujay Kumar Jauhar, Ryen W. White

ACM Trans. Inf. Syst., 2022

Heterogeneous relational reasoning in knowledge graphs with reinforcement learning.

Mandana Saebi, Steven Kreig, Chuxu Zhang, Meng Jiang, Tomasz Kajdanowicz, Nitesh V. Chawla

Inf. Fusion, 2022

Editorial: Computational Behavioral Modeling for Big User Data.

Meng Jiang, Chuxu Zhang, Xiangliang Zhang, Neil Shah

Frontiers Big Data, 2022

Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning.

Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang

CoRR, 2022

Contrastive Graph Few-Shot Learning.

Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang

CoRR, 2022

Adversarial Cross-View Disentangled Graph Contrastive Learning.

Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang

CoRR, 2022

NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs.

Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla

CoRR, 2022

Graph-based Molecular Representation Learning.

Zhichun Guo, Bozhao Nan, Yijun Tian, Olaf Wiest, Chuxu Zhang, Nitesh V. Chawla

CoRR, 2022

Few-Shot Learning on Graphs: A Survey.

Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu

CoRR, 2022

Interpretable Relation Learning on Heterogeneous Graphs.

Qiang Yang, Qiannan Zhang, Chuxu Zhang, Xiangliang Zhang

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

HG-Meta: Graph Meta-learning over Heterogeneous Graphs.

Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Heterogeneous Temporal Graph Neural Network.

Yujie Fan, Mingxuan Ju, Chuxu Zhang, Yanfang Ye

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Adapting Distilled Knowledge for Few-shot Relation Reasoning over Knowledge Graphs.

Yiming Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Label-invariant Augmentation for Semi-Supervised Graph Classification.

Han Yue, Chunhui Zhang, Chuxu Zhang, Hongfu Liu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Co-Modality Graph Contrastive Learning for Imbalanced Node Classification.

Yiyue Qian, Chunhui Zhang, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer.

Qiannan Zhang, Xiaodong Wu, Qiang Yang, Chuxu Zhang, Xiangliang Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Self-Supervised Hypergraph Transformer for Recommender Systems.

Lianghao Xia, Chao Huang, Chuxu Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Disentangled Dynamic Heterogeneous Graph Learning for Opioid Overdose Prediction.

Qianlong Wen, Zhongyu Ouyang, Jianfei Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Task-Adaptive Few-shot Node Classification.

Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning.

Yiyue Qian, Yiming Zhang, Qianlong Wen, Yanfang Ye, Chuxu Zhang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Toward Graph Minimally-Supervised Learning.

Kaize Ding, Chuxu Zhang, Jie Tang, Nitesh V. Chawla, Huan Liu

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Rx-refill Graph Neural Network to Reduce Drug Overprescribing Risks (Extended Abstract).

Jianfei Zhang, Ai-Te Kuo, Jianan Zhao, Qianlong Wen, Erin L. Winstanley, Chuxu Zhang, Yanfang Ye

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Few-Shot Learning on Graphs.

Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks.

Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald A. Metoyer, Nitesh V. Chawla

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation.

Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald A. Metoyer, Nitesh V. Chawla

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

GraphBERT: Bridging Graph and Text for Malicious Behavior Detection on Social Media.

Jiele Wu, Chunhui Zhang, Zheyuan Liu, Erchi Zhang, Steven Wilson, Chuxu Zhang

Proceedings of the IEEE International Conference on Data Mining, 2022

Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering.

Mingxuan Ju, Wenhao Yu, Tong Zhao, Chuxu Zhang, Yanfang Ye

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation.

Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, Chuxu Zhang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Malicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning.

Yiyue Qian, Yiming Zhang, Nitesh V. Chawla, Yanfang Ye, Chuxu Zhang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

A Biased Sampling Method for Imbalanced Personalized Ranking.

Lu Yu, Shichao Pei, Feng Zhu, Longfei Li, Jun Zhou, Chuxu Zhang, Xiangliang Zhang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

SAIL: Self-Augmented Graph Contrastive Learning.

Lu Yu, Shichao Pei, Lizhong Ding, Jun Zhou, Longfei Li, Chuxu Zhang, Xiangliang Zhang

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Inductive Contextual Relation Learning for Personalization.

Chuxu Zhang, Huaxiu Yao, Lu Yu, Chao Huang, Dongjin Song, Haifeng Chen, Meng Jiang, Nitesh V. Chawla

ACM Trans. Inf. Syst., 2021

Recipe Recommendation With Hierarchical Graph Attention Network.

Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla

Frontiers Big Data, 2021

Heterogeneous Temporal Graph Neural Network.

Yujie Fan, Mingxuan Ju, Chuxu Zhang, Liang Zhao, Yanfang Ye

CoRR, 2021

Few-Shot Graph Learning for Molecular Property Prediction.

Zhichun Guo, Chuxu Zhang, Wenhao Yu, John Herr, Olaf Wiest, Meng Jiang, Nitesh V. Chawla

Proceedings of the WWW '21: The Web Conference 2021, 2021

Multi-view Self-supervised Heterogeneous Graph Embedding.

Jianan Zhao, Qianlong Wen, Shiyu Sun, Yanfang Ye, Chuxu Zhang

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media.

Yiyue Qian, Yiming Zhang, Yanfang Ye, Chuxu Zhang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Data Efficient Learning on Graphs.

Chuxu Zhang, Jundong Li, Meng Jiang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Adapting Meta Knowledge with Heterogeneous Information Network for COVID-19 Themed Malicious Repository Detection.

Yiyue Qian, Yiming Zhang, Yanfang Ye, Chuxu Zhang

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

RxNet: Rx-refill Graph Neural Network for Overprescribing Detection.

Jianfei Zhang, Ai-Te Kuo, Jianan Zhao, Qianlong Wen, Erin L. Winstanley, Chuxu Zhang, Yanfang Ye

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Recipe Representation Learning with Networks.

Yijun Tian, Chuxu Zhang, Ronald A. Metoyer, Nitesh V. Chawla

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Self-supervised Smoothing Graph Neural Networks.

Lu Yu, Shichao Pei, Chuxu Zhang, Lizhong Ding, Jun Zhou, Longfei Li, Xiangliang Zhang

CoRR, 2020

Addressing Class-Imbalance Problem in Personalized Ranking.

Lu Yu, Shichao Pei, Chuxu Zhang, Shangsong Liang, Xiao Bai, Xiangliang Zhang

CoRR, 2020

Heterogeneous Relational Reasoning in Knowledge Graphs with Reinforcement Learning.

Mandana Saebi, Steven J. Krieg, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla

CoRR, 2020

Hierarchically Structured Transformer Networks for Fine-Grained Spatial Event Forecasting.

Xian Wu, Chao Huang, Chuxu Zhang, Nitesh V. Chawla

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Learning from Heterogeneous Networks: Methods and Applications.

Chuxu Zhang

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Multi-modal Network Representation Learning.

Chuxu Zhang, Meng Jiang, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Cross-Interaction Hierarchical Attention Networks for Urban Anomaly Prediction.

Chao Huang, Chuxu Zhang, Peng Dai, Liefeng Bo

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Few-Shot Multi-Hop Relation Reasoning over Knowledge Bases.

Chuxu Zhang, Lu Yu, Mandana Saebi, Meng Jiang, Nitesh V. Chawla

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

GraSeq: Graph and Sequence Fusion Learning for Molecular Property Prediction.

Zhichun Guo, Wenhao Yu, Chuxu Zhang, Meng Jiang, Nitesh V. Chawla

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Few-Shot Knowledge Graph Completion.

Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, Nitesh V. Chawla

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Graph Few-Shot Learning via Knowledge Transfer.

Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

MiST: A Multiview and Multimodal Spatial-Temporal Learning Framework for Citywide Abnormal Event Forecasting.

Chao Huang, Chuxu Zhang, Jiashu Zhao, Xian Wu, Nitesh V. Chawla, Dawei Yin

Proceedings of the World Wide Web Conference, 2019

SHNE: Representation Learning for Semantic-Associated Heterogeneous Networks.

Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla

Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, 2019

Heterogeneous Graph Neural Network.

Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics.

Chao Huang, Xian Wu, Xuchao Zhang, Chuxu Zhang, Jiashu Zhao, Dawei Yin, Nitesh V. Chawla

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Deep Dynamic Fusion Network for Traffic Accident Forecasting.

Chao Huang, Chuxu Zhang, Peng Dai, Liefeng Bo

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.

Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

Multi-Order Attentive Ranking Model for Sequential Recommendation.

Lu Yu, Chuxu Zhang, Shangsong Liang, Xiangliang Zhang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

CARL: Content-Aware Representation Learning for Heterogeneous Networks.

Chuxu Zhang, Ananthram Swami, Nitesh V. Chawla

CoRR, 2018

Camel: Content-Aware and Meta-path Augmented Metric Learning for Author Identification.

Chuxu Zhang, Chao Huang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Task-Guided and Semantic-Aware Ranking for Academic Author-Paper Correlation Inference.

Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

WalkRanker: A Unified Pairwise Ranking Model With Multiple Relations for Item Recommendation.

Lu Yu, Chuxu Zhang, Shichao Pei, Guolei Sun, Xiangliang Zhang

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Collaborative User Network Embedding for Social Recommender Systems.

Chuxu Zhang, Lu Yu, Yan Wang, Chirag Shah, Xiangliang Zhang

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

ImWalkMF: Joint matrix factorization and implicit walk integrative learning for recommendation.

Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh V. Chawla

Proceedings of the 2017 IEEE International Conference on Big Data (IEEE BigData 2017), 2017

A Community-Aware Approach to Minimizing Dissemination in Graphs.

Chuxu Zhang, Lu Yu, Chuang Liu, Zi-Ke Zhang, Tao Zhou

Proceedings of the Web and Big Data - First International Joint Conference, 2017

Identifying the Academic Rising Stars via Pairwise Citation Increment Ranking.

Chuxu Zhang, Chuang Liu, Lu Yu, Zi-Ke Zhang, Tao Zhou

Proceedings of the Web and Big Data - First International Joint Conference, 2017

2016

Identifying the Academic Rising Stars.

Chuxu Zhang, Chuang Liu, Lu Yu, Zi-Ke Zhang, Tao Zhou

CoRR, 2016

AdaWIRL: A Novel Bayesian Ranking Approach for Personal Big-Hit Paper Prediction.

Chuxu Zhang, Lu Yu, Jie Lu, Tao Zhou, Zi-Ke Zhang

Proceedings of the Web-Age Information Management - 17th International Conference, 2016

RankMBPR: Rank-Aware Mutual Bayesian Personalized Ranking for Item Recommendation.

Lu Yu, Ge Zhou, Chu-Xu Zhang, Junming Huang, Chuang Liu, Zi-Ke Zhang

Proceedings of the Web-Age Information Management - 17th International Conference, 2016

2015

A Novel Approach for Generating Personalized Mention List on Micro-Blogging System.

Ge Zhou, Lu Yu, Chu-Xu Zhang, Chuang Liu, Zi-Ke Zhang, Jianlin Zhang

Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

2013

Information Filtering via Collaborative User Clustering Modeling.

Chu-Xu Zhang, Zi-Ke Zhang, Lu Yu, Chuang Liu, Hao Liu, Xiao-Yong Yan

CoRR, 2013

Emergence of Blind Areas in Information Spreading.

Zi-Ke Zhang, Chu-Xu Zhang, Xiao-Pu Han, Chuang Liu

CoRR, 2013

Epidemic Spreading on Weighted Complex Networks.

Ye Sun, Chuang Liu, Chu-Xu Zhang, Zi-Ke Zhang

CoRR, 2013

2012

An Evolving model of online bipartite networks

Chu-Xu Zhang, Zi-Ke Zhang, Chuang Liu

CoRR, 2012