Chao Huang

According to our database, Chao Huang authored at least 134 papers between 2015 and 2024.

Collaborative distances:

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

2024

Trajectory-User Linking via Hierarchical Spatio-Temporal Attention Networks.

Wei Chen, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong

ACM Trans. Knowl. Discov. Data, May, 2024

Multi-Behavior Graph Neural Networks for Recommender System.

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo

IEEE Trans. Neural Networks Learn. Syst., April, 2024

Graph Augmentation for Recommendation.

Qianru Zhang, Lianghao Xia, Xuheng Cai, Siu-Ming Yiu, Chao Huang, Christian S. Jensen

CoRR, 2024

Dual-Channel Multiplex Graph Neural Networks for Recommendation.

Xiang Li, Chaofan Fu, Zhongying Zhao, Guanjie Zheng, Chao Huang, Junyu Dong, Yanwei Yu

CoRR, 2024

OpenGraph: Towards Open Graph Foundation Models.

Lianghao Xia, Ben Kao, Chao Huang

CoRR, 2024

UrbanGPT: Spatio-Temporal Large Language Models.

Zhonghang Li, Lianghao Xia, Jiabin Tang, Yong Xu, Lei Shi, Long Xia, Dawei Yin, Chao Huang

CoRR, 2024

PromptMM: Multi-Modal Knowledge Distillation for Recommendation with Prompt-Tuning.

Wei Wei, Jiabin Tang, Yangqin Jiang, Lianghao Xia, Chao Huang

CoRR, 2024

HiGPT: Heterogeneous Graph Language Model.

Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Long Xia, Dawei Yin, Chao Huang

CoRR, 2024

GraphEdit: Large Language Models for Graph Structure Learning.

Zirui Guo, Lianghao Xia, Yanhua Yu, Yuling Wang, Zixuan Yang, Wei Wei, Liang Pang, Tat-Seng Chua, Chao Huang

CoRR, 2024

LLMRec: Large Language Models with Graph Augmentation for Recommendation.

Wei Wei, Xubin Ren, Jiabin Tang, Qinyong Wang, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

SSLRec: A Self-Supervised Learning Framework for Recommendation.

Xubin Ren, Lianghao Xia, Yuhao Yang, Wei Wei, Tianle Wang, Xuheng Cai, Chao Huang

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

DiffKG: Knowledge Graph Diffusion Model for Recommendation.

Yangqin Jiang, Yuhao Yang, Lianghao Xia, Chao Huang

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

Multi-Behavior Sequential Recommendation With Temporal Graph Transformer.

Lianghao Xia, Chao Huang, Yong Xu, Jian Pei

IEEE Trans. Knowl. Data Eng., June, 2023

Dynamic Multi-View Graph Neural Networks for Citywide Traffic Inference.

Shaojie Dai, Jinshuai Wang, Chao Huang, Yanwei Yu, Junyu Dong

ACM Trans. Knowl. Discov. Data, May, 2023

Robust anomaly detection for multivariate time series through temporal GCNs and attention-based VAE.

Yunfei Shi, Bin Wang, Yanwei Yu, Xianfeng Tang, Chao Huang, Junyu Dong

Knowl. Based Syst., 2023

Graph Pre-training and Prompt Learning for Recommendation.

Yuhao Yang, Lianghao Xia, Da Luo, Kangyi Lin, Chao Huang

CoRR, 2023

Self-Supervised Deconfounding Against Spatio-Temporal Shifts: Theory and Modeling.

Jiahao Ji, Wentao Zhang, Jingyuan Wang, Yue He, Chao Huang

CoRR, 2023

GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks.

Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang

CoRR, 2023

Representation Learning with Large Language Models for Recommendation.

Xubin Ren, Wei Wei, Lianghao Xia, Lixin Su, Suqi Cheng, Junfeng Wang, Dawei Yin, Chao Huang

CoRR, 2023

GraphGPT: Graph Instruction Tuning for Large Language Models.

Jiabin Tang, Yuhao Yang, Wei Wei, Lei Shi, Lixin Su, Suqi Cheng, Dawei Yin, Chao Huang

CoRR, 2023

SSLRec: A Self-Supervised Learning Library for Recommendation.

Xubin Ren, Lianghao Xia, Yuhao Yang, Wei Wei, Tianle Wang, Xuheng Cai, Chao Huang

CoRR, 2023

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting.

Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann

CoRR, 2023

Adaptive Graph Contrastive Learning for Recommendation.

Yangqin Jiang, Chao Huang, Lianghao Xia

CoRR, 2023

Do We Really Need Graph Neural Networks for Traffic Forecasting?

Xu Liu, Yuxuan Liang, Chao Huang, Hengchang Hu, Yushi Cao, Bryan Hooi, Roger Zimmermann

CoRR, 2023

Automated Spatio-Temporal Graph Contrastive Learning.

Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Zhonghang Li, Siu-Ming Yiu

Proceedings of the ACM Web Conference 2023, 2023

Debiased Contrastive Learning for Sequential Recommendation.

Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang, Da Luo, Kangyi Lin

Proceedings of the ACM Web Conference 2023, 2023

Graph-less Collaborative Filtering.

Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu

Proceedings of the ACM Web Conference 2023, 2023

Automated Self-Supervised Learning for Recommendation.

Lianghao Xia, Chao Huang, Chunzhen Huang, Kangyi Lin, Tao Yu, Ben Kao

Proceedings of the ACM Web Conference 2023, 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

Heterogeneous Graph Contrastive Learning for Recommendation.

Mengru Chen, Chao Huang, Lianghao Xia, Wei Wei, Yong Xu, Ronghua Luo

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

Graph Masked Autoencoder for Sequential Recommendation.

Yaowen Ye, Lianghao Xia, Chao Huang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Disentangled Contrastive Collaborative Filtering.

Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, Chao Huang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Graph Transformer for Recommendation.

Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, Chao Huang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Multi-Relational Contrastive Learning for Recommendation.

Wei Wei, Lianghao Xia, Chao Huang

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting.

Xu Liu, Yutong Xia, Yuxuan Liang, Junfeng Hu, Yiwei Wang, Lei Bai, Chao Huang, Zhenguang Liu, Bryan Hooi, Roger Zimmermann

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks.

Zhonghang Li, Lianghao Xia, Yong Xu, Chao Huang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Knowledge Graph Self-Supervised Rationalization for Recommendation.

Yuhao Yang, Chao Huang, Lianghao Xia, Chunzhen Huang

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

Adaptive Graph Contrastive Learning for Recommendation.

Yangqin Jiang, Chao Huang, Lianghao Huang

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

Multiplex Heterogeneous Graph Neural Network with Behavior Pattern Modeling.

Chaofan Fu, Guanjie Zheng, Chao Huang, Yanwei Yu, Junyu Dong

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

Denoised Self-Augmented Learning for Social Recommendation.

Tianle Wang, Lianghao Xia, Chao Huang

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

Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation.

Qianru Zhang, Chao Huang, Lianghao Xia, Zheng Wang, Siu Ming Yiu, Ruihua Han

Proceedings of the International Conference on Machine Learning, 2023

LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation.

Xuheng Cai, Chao Huang, Lianghao Xia, Xubin Ren

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Disentangled Graph Social Recommendation.

Lianghao Xia, Yizhen Shao, Chao Huang, Yong Xu, Huance Xu, Jian Pei

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Explainable Spatio-Temporal Graph Neural Networks.

Jiabin Tang, Lianghao Xia, Chao Huang

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

Spatio-Temporal Meta Contrastive Learning.

Jiabin Tang, Lianghao Xia, Jie Hu, Chao Huang

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

How Expressive are Graph Neural Networks in Recommendation?

Xuheng Cai, Lianghao Xia, Xubin Ren, Chao Huang

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

Graph Structure Learning on User Mobility Data for Social Relationship Inference.

Guangming Qin, Lexue Song, Yanwei Yu, Chao Huang, Wenzhe Jia, Yuan Cao, Junyu Dong

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

Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction.

Jiahao Ji, Jingyuan Wang, Chao Huang, Junjie Wu, Boren Xu, Zhenhe Wu, Junbo Zhang, Yu Zheng

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

2022

Collaborative Reflection-Augmented Autoencoder Network for Recommender Systems.

Lianghao Xia, Chao Huang, Yong Xu, Huance Xu, Xiang Li, Weiguo Zhang

ACM Trans. Inf. Syst., 2022

Representation Learning on Variable Length and Incomplete Wearable-Sensory Time Series.

Xian Wu, Chao Huang, Pablo Robles-Granda, Nitesh V. Chawla

ACM Trans. Intell. Syst. Technol., 2022

Heterogeneous graph neural network for attribute completion.

Kai Wang, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong

Knowl. Based Syst., 2022

Online Anomalous Subtrajectory Detection on Road Networks with Deep Reinforcement Learning.

Qianru Zhang, Zheng Wang, Cheng Long, Chao Huang, Siu-Ming Yiu, Yiding Liu, Gao Cong, Jieming Shi

CoRR, 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

Spatial-Temporal Sequential Hypergraph Network for Crime Prediction.

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo, Xiyue Zhang, Tianyi Chen

CoRR, 2022

Contrastive Meta Learning with Behavior Multiplicity for Recommendation.

Wei Wei, Chao Huang, Lianghao Xia, Yong Xu, Jiashu Zhao, Dawei Yin

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

Knowledge Graph Contrastive Learning for Recommendation.

Yuhao Yang, Chao Huang, Lianghao Xia, Chenliang Li

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Hypergraph Contrastive Collaborative Filtering.

Lianghao Xia, Chao Huang, Yong Xu, Jiashu Zhao, Dawei Yin, Jimmy X. Huang

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Self-Supervised Learning for Recommender System.

Chao Huang, Xiang Wang, Xiangnan He, Dawei Yin

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Multiplex Heterogeneous Graph Convolutional Network.

Pengyang Yu, Chaofan Fu, Yanwei Yu, Chao Huang, Zhongying Zhao, Junyu Dong

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

Multi-Behavior Hypergraph-Enhanced Transformer for Sequential Recommendation.

Yuhao Yang, Chao Huang, Lianghao Xia, Yuxuan Liang, Yanwei Yu, Chenliang Li

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

Mutual Distillation Learning Network for Trajectory-User Linking.

Wei Chen, Shuzhe Li, Chao Huang, Yanwei Yu, Yongguo Jiang, Junyu Dong

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

Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction.

Zhonghang Li, Chao Huang, Lianghao Xia, Yong Xu, Jian Pei

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Scalable Motif Counting for Large-scale Temporal Graphs.

Zhongqiang Gao, Chuanqi Cheng, Yanwei Yu, Lei Cao, Chao Huang, Junyu Dong

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

When do contrastive learning signals help spatio-temporal graph forecasting?

Xu Liu, Yuxuan Liang, Chao Huang, Yu Zheng, Bryan Hooi, Roger Zimmermann

Proceedings of the 30th International Conference on Advances in Geographic Information Systems, 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

Self-Supervised Learning for Recommendation.

Chao Huang, Lianghao Xia, Xiang Wang, Xiangnan He, Dawei Yin

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

Motif-Preserving Dynamic Attributed Network Embedding.

Zhijun Liu, Chao Huang, Yanwei Yu, Junyu Dong

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

Graph Meta Network for Multi-Behavior Recommendation.

Lianghao Xia, Yong Xu, Chao Huang, Peng Dai, Liefeng Bo

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning.

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Liefeng Bo, Xiyue Zhang, Tianyi Chen

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

Temporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference.

Shaojie Dai, Jinshuai Wang, Chao Huang, Yanwei Yu, Junyu Dong

Proceedings of the IEEE International Conference on Data Mining, 2021

Multi-Behavior Enhanced Recommendation with Cross-Interaction Collaborative Relation Modeling.

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Mengyin Lu, Liefeng Bo

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Purchase Intent Forecasting with Convolutional Hierarchical Transformer Networks.

Chao Huang, Jiashu Zhao, Dawei Yin

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Social Recommendation with Self-Supervised Metagraph Informax Network.

Xiaoling Long, Chao Huang, Yong Xu, Huance Xu, Peng Dai, Lianghao Xia, Liefeng Bo

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

Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network.

Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia, Peng Dai, Liefeng Bo, Junbo Zhang, Yu Zheng

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation.

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Xiyue Zhang, Hongsheng Yang, Jian Pei, Liefeng Bo

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Knowledge-aware Coupled Graph Neural Network for Social Recommendation.

Chao Huang, Huance Xu, Yong Xu, Peng Dai, Lianghao Xia, Mengyin Lu, Liefeng Bo, Hao Xing, Xiaoping Lai, Yanfang Ye

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Graph-Enhanced Multi-Task Learning of Multi-Level Transition Dynamics for Session-based Recommendation.

Chao Huang, Jiahui Chen, Lianghao Xia, Yong Xu, Peng Dai, Yanqing Chen, Liefeng Bo, Jiashu Zhao, Jimmy Xiangji Huang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

On Physical-Social-Aware Localness Inference by Exploring Big Data from Location-Based Services.

Chao Huang, Dong Wang, Jun Tao, Brian Mann

IEEE Trans. Big Data, 2020

Scalable Uncertainty-Aware Truth Discovery in Big Data Social Sensing Applications for Cyber-Physical Systems.

Chao Huang, Dong Wang, Nitesh V. Chawla

IEEE Trans. Big Data, 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

Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network.

Lianghao Xia, Chao Huang, Yong Xu, Peng Dai, Bo Zhang, Liefeng Bo

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 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

Global Context Enhanced Social Recommendation with Hierarchical Graph Neural Networks.

Huance Xu, Chao Huang, Yong Xu, Lianghao Xia, Hao Xing, Dawei Yin

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Joint Modeling of Local and Global Behavior Dynamics for Session-Based Recommendation.

Yong Xu, Jiahui Chen, Chao Huang, Bo Zhang, Hao Xing, Peng Dai, Liefeng Bo

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Spatial-Temporal Convolutional Graph Attention Networks for Citywide Traffic Flow Forecasting.

Xiyue Zhang, Chao Huang, Yong Xu, Lianghao Xia

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

Personalized Imputation on Wearable-Sensory Time Series via Knowledge Transfer.

Xian Wu, Stephen M. Mattingly, Shayan Mirjafari, Chao Huang, Nitesh V. Chawla

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

Fast Attributed Multiplex Heterogeneous Network Embedding.

Zhijun Liu, Chao Huang, Yanwei Yu, Baode Fan, Junyu Dong

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

Dynamic Representation Learning for Large-Scale Attributed Networks.

Zhijun Liu, Chao Huang, Yanwei Yu, Peng Song, Baode Fan, Junyu Dong

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

2019

Heterogeneous Deep Graph Infomax.

Yuxiang Ren, Bo Liu, Chao Huang, Peng Dai, Liefeng Bo, Jiawei Zhang

CoRR, 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

Neural Tensor Factorization for Temporal Interaction Learning.

Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, 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

Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity.

Chao Huang, Xian Wu, Xuchao Zhang, Suwen Lin, Nitesh V. Chawla

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

Similarity-Aware Network Embedding with Self-Paced Learning.

Chao Huang, Baoxu Shi, Xuchao Zhang, Xian Wu, Nitesh V. Chawla

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

2018

Who to select: Identifying critical sources in social sensing.

Dong Wang, Nathan Vance, Chao Huang

Knowl. Based Syst., 2018

Neural Tensor Factorization.

Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, 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

Towards Reliable Hypothesis Validation in Social Sensing Applications.

Dong Wang, Daniel Zhang, Chao Huang

Proceedings of the 15th Annual IEEE International Conference on Sensing, 2018

RESTFul: Resolution-Aware Forecasting of Behavioral Time Series Data.

Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Louis Faust, Nitesh V. Chawla

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

DeepCrime: Attentive Hierarchical Recurrent Networks for Crime Prediction.

Chao Huang, Junbo Zhang, Yu Zheng, Nitesh V. Chawla

Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2017

An Unsupervised Approach to Inferring the Localness of People Using Incomplete Geotemporal Online Check-In Data.

Chao Huang, Dong Wang, Jun Tao

ACM Trans. Intell. Syst. Technol., 2017

Toward local family relationship discovery in location-based social network.

Chao Huang, Dong Wang, Shenglong Zhu, Brian Mann

Soc. Netw. Anal. Min., 2017

Towards social-aware interesting place finding in social sensing applications.

Chao Huang, Dong Wang, Brian Mann

Knowl. Based Syst., 2017

Exploring Scalability and Time-Sensitiveness in Reliable Social Sensing With Accuracy Assessment.

Chao Huang, Dong Wang

IEEE Access, 2017

UAPD: Predicting Urban Anomalies from Spatial-Temporal Data.

Xian Wu, Yuxiao Dong, Chao Huang, Jian Xu, Dong Wang, Nitesh V. Chawla

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

Where are you from: Home location profiling of crowd sensors from noisy and sparse crowdsourcing data.

Chao Huang, Dong Wang, Shenglong Zhu

Proceedings of the 2017 IEEE Conference on Computer Communications, 2017

Towards Scalable and Dynamic Social Sensing Using A Distributed Computing Framework.

Daniel Yue Zhang, Chao Zheng, Dong Wang, Douglas Thain, Xin Mu, Greg Madey, Chao Huang

Proceedings of the 37th IEEE International Conference on Distributed Computing Systems, 2017

Critical Source Selection in Social Sensing Applications.

Chao Huang, Dong Wang

Proceedings of the 13th International Conference on Distributed Computing in Sensor Systems, 2017

Reliable fake review detection via modeling temporal and behavioral patterns.

Xian Wu, Yuxiao Dong, Jun Tao, Chao Huang, Nitesh V. Chawla

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

Towards Diversified Local Users Identification Using Location Based Social Networks.

Chao Huang, Dong Wang, Shenglong Zhu

Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, Sydney, Australia, July 31, 2017

2016

Topic-Aware Social Sensing with Arbitrary Source Dependency Graphs.

Chao Huang, Dong Wang

Proceedings of the 15th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2016

Towards Reliable Social Sensing in Cyber-Physical-Social Systems.

Chao Huang, Jermaine Marshall, Dong Wang, Mianxiong Dong

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Theme-Relevant Truth Discovery on Twitter: An Estimation Theoretic Approach.

Dong Wang, Jermaine Marshall, Chao Huang

Proceedings of the Tenth International Conference on Web and Social Media, 2016

Unsupervised Interesting Places Discovery in Location-Based Social Sensing.

Chao Huang, Dong Wang

Proceedings of the International Conference on Distributed Computing in Sensor Systems, 2016

Crowdsourcing-based Urban Anomaly Prediction System for Smart Cities.

Chao Huang, Xian Wu, Dong Wang

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

On robust truth discovery in sparse social media sensing.

Daniel Yue Zhang, Rungang Han, Dong Wang, Chao Huang

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Towards unsupervised home location inference from online social media.

Chao Huang, Dong Wang, Shenglong Zhu, Daniel Yue Zhang

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Exploiting spatial-temporal-social constraints for localness inference using online social media.

Chao Huang, Dong Wang

Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2016

2015

Spatial-Temporal Aware Truth Finding in Big Data Social Sensing Applications.

Chao Huang, Dong Wang

Proceedings of the 2015 IEEE TrustCom/BigDataSE/ISPA, 2015

On Interesting Place Finding in Social Sensing: An Emerging Smart City Application Paradigm.

Chao Huang, Dong Wang

Proceedings of the 2015 IEEE International Conference on Smart City/SocialCom/SustainCom/DataCom/SC2 2015, 2015

Confidence-aware truth estimation in social sensing applications.

Dong Wang, Chao Huang

Proceedings of the 12th Annual IEEE International Conference on Sensing, 2015

On spatial-temporal truth finding in social sensing.

Chao Huang, Dong Wang, Nitesh V. Chawla

Proceedings of the 12th Annual IEEE International Conference on Sensing, 2015

Demo paper: A confidence-aware truth estimation tool for social sensing applications.

Chao Huang, Dong Wang

Proceedings of the 12th Annual IEEE International Conference on Sensing, 2015

Towards Time-Sensitive Truth Discovery in Social Sensing Applications.

Chao Huang, Dong Wang, Nitesh V. Chawla

Proceedings of the 12th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2015

Time-Aware Truth Discovery in Social Sensing.

Chao Huang, Dong Wang

Proceedings of the 12th IEEE International Conference on Mobile Ad Hoc and Sensor Systems, 2015

Link weight based truth discovery in social sensing.

Chao Huang, Dong Wang

Proceedings of the 14th International Conference on Information Processing in Sensor Networks, 2015

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline.

Keith Feldman, Louis Faust, Xian Wu, Chao Huang, Nitesh V. Chawla

Proceedings of the Towards Integrative Machine Learning and Knowledge Extraction, 2015