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FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction Conference paper
Yang, Linghua, Chen, Wantong, He, Xiaoxi, Wei, Shuyue, Xu, Yi, Zhou, Zimu, Tong, Yongxin. FedGTP: Exploiting Inter-Client Spatial Dependency in Federated Graph-based Traffic Prediction[C], New York, NY, USA:Association for Computing Machinery, 2024, 6105–6116.
Authors:  Yang, Linghua;  Chen, Wantong;  He, Xiaoxi;  Wei, Shuyue;  Xu, Yi; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/09/11
Federated Learning  Traffic Prediction  Spatial-temporal Graph Neural Network  
Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks Conference paper
Duan, Wenying, Fang, Tianxiang, Rao, Hong, He, Xiaoxi. Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks[C], New York, NY, USA:Association for Computing Machinery, 2024, 701-712.
Authors:  Duan, Wenying;  Fang, Tianxiang;  Rao, Hong;  He, Xiaoxi
Favorite | TC[Scopus]:0 | Submit date：2024/09/11
Lottery Ticket Hypothesis  Spatial-temporal Data Mining  Spatial-temporal Graph Neural Network  
DyGKT: Dynamic Graph Learning for Knowledge Tracing Conference paper
KE CHENG, LINZHI PENG, PENGYANG WANG, JUNCHEN YE, LEILEI SUN, BOWEN DU. DyGKT: Dynamic Graph Learning for Knowledge Tracing[C], New York, NY, USA:Association for Computing Machinery, 2024, 409-420.
Authors:  KE CHENG;  LINZHI PENG;  PENGYANG WANG;  JUNCHEN YE;  LEILEI SUN; et al.
Favorite | TC[Scopus]:1 | Submit date：2024/08/28
Dynamic Graph  Educational Data Mining  Graph Neural Networks  Knowledge Tracing  
Double Correction Framework for Denoising Recommendation Conference paper
He, Zhuangzhuang, Wang, Yifan, Yang, Yonghui, Sun, Peijie, Wu, Le, Bai, Haoyue, Gong, Jinqi, Hong, Richang, Zhang, Min. Double Correction Framework for Denoising Recommendation[C], New York, NY, USA:Association for Computing Machinery, 2024, 1062-1072.
Authors:  He, Zhuangzhuang;  Wang, Yifan;  Yang, Yonghui;  Sun, Peijie;  Wu, Le; et al.
Favorite | TC[Scopus]:0 | Submit date：2024/10/10
Denoising  Implicit Feedback  Recommendation  
Effective interpretable learning for large-scale categorical data Journal article
Zhang, Yishuo, Zaidi, Nayyar, Zhou, Jiahui, Wang, Tao, Li, Gang. Effective interpretable learning for large-scale categorical data[J]. Data Mining and Knowledge Discovery, 2024, 38(4), 2223-2251.
Authors:  Zhang, Yishuo;  Zaidi, Nayyar;  Zhou, Jiahui;  Wang, Tao;  Li, Gang
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:2.8/5.3 | Submit date：2024/09/03
Discriminative Bayesian Network Models  Feature Engineering  Interpretable Models  Large Categorical Datasets  Low-bias Models  
Assessing GPT-4 Generated Abstracts: Text Relevance and Detectors Based on Faithfulness, Expressiveness, and Elegance Principle Conference paper
Li, Bixuan, Chen, Qifu, Lin, Jinlin, Li, Sai, Yen, Jerome. Assessing GPT-4 Generated Abstracts: Text Relevance and Detectors Based on Faithfulness, Expressiveness, and Elegance Principle[C]:Springer Science and Business Media Deutschland GmbH, 2024, 165-180.
Authors:  Li, Bixuan;  Chen, Qifu;  Lin, Jinlin;  Li, Sai;  Yen, Jerome
Favorite | TC[Scopus]:0 | Submit date：2024/05/16
Abstract Generation  Artificial Intelligence  Chatbot  Gpt-4  Large Language Models  
Dual-stage Flows-based Generative Modeling for Traceable Urban Planning Conference paper
Hu, Xuanming, Fan, Wei, Wang, Dongjie, Wang, Pengyang, Li, Yong, Fu, Yanjie. Dual-stage Flows-based Generative Modeling for Traceable Urban Planning[C]:Society for Industrial and Applied Mathematics Publications, 2024, 370-378.
Authors:  Hu, Xuanming;  Fan, Wei;  Wang, Dongjie;  Wang, Pengyang;  Li, Yong; et al.
Favorite | TC[Scopus]:2 | Submit date：2024/06/05
Flows-based Framework  Generative Ai  Urban Planning  
PERT-GNN: Latency Prediction for Microservice-based Cloud-Native Applications via Graph Neural Networks Conference paper
Da Sun Handason Tam, Yang Liu, Huanle Xu, Siyue Xie, Wing Cheong Lau. PERT-GNN: Latency Prediction for Microservice-based Cloud-Native Applications via Graph Neural Networks[C], 2023, 2155 - 2165.
Authors:  Da Sun Handason Tam;  Yang Liu;  Huanle Xu;  Siyue Xie;  Wing Cheong Lau
Favorite | TC[WOS]:2 TC[Scopus]:5 | Submit date：2023/07/30
Delay Prediction  Microservices  Cloud Computing  Graph Neural Networks  Graph Transformers  Machine Learning  
Localised Adaptive Spatial-Temporal Graph Neural Network Conference paper
Duan, Wenying, He, Xiaoxi, Zhou, Zimu, Thiele, Lothar, Rao, Hong. Localised Adaptive Spatial-Temporal Graph Neural Network[C]:ASSOC COMPUTING MACHINERY1601 Broadway, 10th Floor, NEW YORK, NY, UNITED STATES, 2023, 448-458.
Authors:  Duan, Wenying;  He, Xiaoxi;  Zhou, Zimu;  Thiele, Lothar;  Rao, Hong
Favorite | TC[WOS]:1 TC[Scopus]:7 | Submit date：2024/01/10
Graph Sparsification  Spatial-temporal Data  Spatial-temporal Graph Neural Network  
Semi-supervised Drifted Stream Learning with Short Lookback Conference paper
Weijieying Ren, Pengyang Wang, Xiaolin Li, Charles E. Hughes, Yanjie Fu. Semi-supervised Drifted Stream Learning with Short Lookback[C]:Association for Computing Machinery, 2022, 1504–1513.
Authors:  Weijieying Ren;  Pengyang Wang;  Xiaolin Li;  Charles E. Hughes;  Yanjie Fu
Favorite | TC[WOS]:3 TC[Scopus]:10 | Submit date：2022/07/28
Continual Learning  Distribution Shift  Semi-supervised Learning