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Computer Science

D-Index
35
Citations
7769
World Ranking
11492
National Ranking
1424

Overview

Xiuqiang He is affiliated with Huawei Technologies in China and has contributed extensively to research in computer science with a focus on artificial intelligence and information systems. They have published 193 works mainly in the field of computer science, with specific contributions spanning artificial intelligence, information systems, computer vision and pattern recognition, management science and operations research, and computer networks and communications.

Their research interests include several prominent topics, notably recommender systems and techniques, advanced graph neural networks, topic modeling, advanced bandit algorithms research, domain adaptation and few-shot learning, caching and content delivery, and machine learning and data classification.

Frequent coauthors of Xiuqiang He include Ruiming Tang, Dugang Liu, Xing Tang, Zhenhua Dong, and Weinan Zhang, indicating ongoing collaboration within a network of researchers with complementary expertise.

The venues where Xiuqiang He has most often published include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • ACM Transactions on Information Systems
  • Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • IEEE Transactions on Knowledge and Data Engineering

Significant recent publications by Xiuqiang He include:

  • "Graph Heterogeneous Multi-Relational Recommendation," 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "State representation modeling for deep reinforcement learning based recommendation," 2020, Knowledge-Based Systems
  • "Improving Knowledge Tracing with Collaborative Information," 2022, Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
  • "Less Is Better: Unweighted Data Subsampling via Influence Function," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction," 2020, arXiv (Cornell University)

Best Publications

  • DeepFM: a factorization-machine based neural network for CTR prediction

    Huifeng Guo;Ruiming Tang;Yunming Ye;Zhenguo Li

  • DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

    Huifeng Guo;Ruiming Tang;Yunming Ye;Zhenguo Li

  • UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation

    Kelong Mao;Jieming Zhu;Xi Xiao;Biao Lu

  • Federated Meta-Learning with Fast Convergence and Efficient Communication

    Fei Chen;Mi Luo;Zhenhua Dong;Zhenguo Li

  • Product-Based Neural Networks for User Response Prediction over Multi-Field Categorical Data

    Yanru Qu;Bohui Fang;Weinan Zhang;Ruiming Tang

  • AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

    Bin Liu;Chenxu Zhu;Guilin Li;Weinan Zhang

  • A General Knowledge Distillation Framework for Counterfactual Recommendation via Uniform Data

    Dugang Liu;Pengxiang Cheng;Zhenhua Dong;Xiuqiang He

  • Graph Heterogeneous Multi-Relational Recommendation

    Chong Chen;Weizhi Ma;Min Zhang;Zhaowei Wang

  • Transient Stability Analysis and Enhancement of Renewable Energy Conversion System During LVRT

    Xiuqiang He;Hua Geng;Ruiqi Li;Bikash Chandra Pal

  • Neighbor Interaction Aware Graph Convolution Networks for Recommendation

    Jianing Sun;Yingxue Zhang;Wei Guo;Huifeng Guo

  • Interactive Recommender System via Knowledge Graph-enhanced Reinforcement Learning

    Sijin Zhou;Xinyi Dai;Haokun Chen;Weinan Zhang

  • SimpleX: A Simple and Strong Baseline for Collaborative Filtering

    Kelong Mao;Jieming Zhu;Jinpeng Wang;Quanyu Dai

  • Multi-graph Convolution Collaborative Filtering

    Jianing Sun;Yingxue Zhang;Chen Ma;Mark Coates

  • Federated Meta-Learning for Recommendation

    Fei Chen;Zhenhua Dong;Zhenguo Li;Xiuqiang He

  • Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding

    Zhu Zhang;Zhou Zhao;Zhijie Lin;jieming zhu

  • Open Benchmarking for Click-Through Rate Prediction

    Jieming Zhu;Jinyang Liu;Shuai Yang;Qi Zhang

  • Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos

    Zhu Zhang;Zhijie Lin;Zhou Zhao;Jieming Zhu

  • UNBERT: User-News Matching BERT for News Recommendation.

    Qi Zhang;Jingjie Li;Qinglin Jia;Chuyuan Wang

  • A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks

    Jianing Sun;Wei Guo;Dengcheng Zhang;Yingxue Zhang

  • Deep Learning for Click-Through Rate Estimation

    Weinan Zhang;Jiarui Qin;Wei Guo;Ruiming Tang

  • Mitigating Confounding Bias in Recommendation via Information Bottleneck

    Dugang Liu;Pengxiang Cheng;Hong Zhu;Zhenhua Dong

  • A Generalized Design Framework of Notch Filter Based Frequency-Locked Loop for Three-Phase Grid Voltage

    Xiuqiang He;Hua Geng;Geng Yang

Frequent Co-Authors

Weinan Zhang
Weinan Zhang Shanghai Jiao Tong University
Hua Geng
Hua Geng Tsinghua University
Zhenguo Li
Zhenguo Li Huawei Technologies (China)
Yong Yu
Yong Yu Shanghai Jiao Tong University
Yunming Ye
Yunming Ye Harbin Institute of Technology
Zhou Zhao
Zhou Zhao Zhejiang University
Geng Yang
Geng Yang Tsinghua University
Jun Wang
Jun Wang University College London
Mark Coates
Mark Coates McGill University
Xue Liu
Xue Liu McGill University

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