Yankai Chen

陈焱凯

Postdoctoral Associate

Publications

Google Scholar - DBLP

2024

  1. Towards Effective Top-N Hamming Search via Bipartite Graph Contrastive Hashing
    Yankai Chen, Yixiang Fang, Yifei Zhang, Chenhao Ma, Yang Hong, Irwin King
    IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.
    [paper] [codes]

  2. EASE: Learning Lightweight Semantic Feature Adapters from Large Language Models for CTR Prediction
    Zexuan Qiu, Jieming Zhu, Yankai Chen, Guohao Cai, Weiwen Liu, Zhenhua Dong, Irwin King
    The 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, USA, 2024.
    [paper]

  3. Effective Job-market Mobility Prediction with Attentive Heterogeneous Knowledge Learning and Synergy
    Sida Lin, Zhouyi Zhang, Yankai Chen*, Chenhao Ma*, Yixiang Fang, Shan Dai, Guangli Lu (* indicates corresponding authorship)
    The 33rd ACM International Conference on Information and Knowledge Management (CIKM), Boise, USA, 2024.
    [paper]

  4. Shopping Trajectory Representation Learning with Pre-training for E-commerce Customer Understanding and Recommendation
    Yankai Chen, Quoc-Tuan Truong, Xin Shen, Jin Li, Irwin King
    The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), Oral Presentation, Barcelona, Spain, 2024.
    [paper] [codes]

  5. Geometric View of Soft Decorrelation in Self-Supervised Learning
    Yifei Zhang, Hao Zhu, Zixing Song, Yankai Chen, Xinyu Fu, Ziqiao Meng, Piotr Koniusz, Irwin King
    The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), Oral Presentation, Barcelona, Spain, 2024.
    [paper]

  6. A Survey on Deep Active Learning: Recent Advances and New Frontiers
    Dongyuan Li, Zhen Wang, Yankai Chen, Renhe Jiang, Weiping Ding, Manabu Okumura
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024
    [paper]

  7. Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks
    Yankai Chen, Yixiang Fang, Qiongyan Wang, Xin Cao, Irwin King
    In Proceeding of AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024.
    [paper] [codes]

  8. Influential Exemplar Replay for Incremental Learning in Recommender Systems
    Xinni Zhang, Yankai Chen, Chenhao Ma, Yixiang Fang, Irwin King
    In Proceeding of AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024.
    [arxiv]

  9. HiHPQ: Hierarchical Hyperbolic Product Quantization for Unsupervised Image Retrieval
    Zexuan Qiu, Jiahong Liu, Yankai Chen, Irwin King
    In Proceeding of AAAI Conference on Artificial Intelligence (AAAI), Vancouver, Canada, 2024.
    [paper] [codes]

2023

  1. Mitigating the Popularity Bias of Graph Collaborative Filtering: A Dimensional Collapse Perspective
    Yifei Zhang, Hao Zhu, Yankai Chen, Zixing Song, Piotr Koniusz, Irwin King.
    in Proceeding of Advances in Neural Information Processing Systems (NeurIPS) 36, Spotlight, New Orleans, LA, USA, 2023.
    [paper]

  2. Topological Representation Learning for E-commerce Shopping Behaviors
    Yankai Chen, Quoc-Tuan Truong, Xin Shen, Ming Wang, Jin Li, Jim Chan, Irwin King
    Workshop on Mining and Learning with Graphs at The 29th SIGKDD Conference on Knowledge Discovery and Data Mining (MLG@KDD). Long Beach, LA, USA, 2023.
    [paper]

  3. Contrastive Cross-scale Graph Knowledge Synergy
    Yifei Zhang, Yankai Chen, Zixing Song, Irwin King
    In Proceeding of the 29th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), Oral Presentation, Long Beach, LA, USA, 2023.
    [paper]

  4. A Survey on Graph Embedding Techniques for Biomedical Data: Methods and Applications
    Yaozu Wu#, Yankai Chen#, Zhishuai Yin, Weiping Ding, Irwin King (# indicates equal contribution)
    In Journal of Information Fusion. 2023. Impact Factor: 17.564
    [paper]

  5. WSFE: Wasserstein Sub-graph Feature Encoder for Effective User Segmentation in Collaborative Filtering
    Yankai Chen, Yifei Zhang, Menglin Yang, Zixing Song, Chen Ma, Irwin King.
    In Proceeding of the 46th SIGIR Conference on Research and Development in Information Retrieval (SIGIR). Taipei, Taiwan, China, 2023.
    [paper][codes]

  6. Hierarchical Learning in Hyperbolic Space: Revisit and Beyond
    Menglin Yang, Min Zhou, Rex Ying, Yankai Chen, Irwin King
    In Proceeding of the 40th International Conference on Machine Learning (ICML). Hawaii, USA, 2023.
    [paper]

  7. Bipartite Graph Convolutional Hashing for Effective and Efficient Top-N Search in Hamming Space
    Yankai Chen, Yixiang Fang, Yifei Zhang, Irwin King.
    In Proceeding of the ACM Web Conference (WWW), Oral Presentation, Austin, Texas, USA, 2023.
    [paper][codes]

2022

  1. Learning Binarized Graph Representations with Multi-faceted Quantization Reinforcement for Top-K Recommendation
    Yankai Chen, Huifeng Guo, Yingxue Zhang, Chen Ma, Ruiming Tang, Jingjie Li, Irwin King
    In Proceeding of the 28th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), Oral Presentation, Washington DC, USA, 2022.
    [paper][codes]

  2. An Effective Post-training Embedding Binarization Approach for Fast Online Top-K Passage Matching
    Yankai Chen, Yifei Zhang, Huifeng Guo, Ruiming Tang, Irwin King
    In Proceeding of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL), Taipei, Taiwan, China, 2022.
    [paper]

  3. Attentive Knowledge-aware Graph Convolutional Networks with Collaborative Guidance for Personalized Recommendation
    Yankai Chen, Yaming Yang, Yujing Wang, Jing Bai, Xiangchen Song, Irwin King
    In Proceeding of the 38th IEEE International Conference on Data Engineering (ICDE), Oral Presentation, (Virtual) Kuala Lumpur, Malaysia, 2022.
    [paper][codes]

  4. Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation
    Yankai Chen, Menglin Yang, Yingxue Zhang, Mengchen Zhao, Ziqiao Meng, Jianye Hao, Irwin King
    In Proceeding of the 15th International Conference on Web Search and Data Mining (WSDM), Oral Presentation, (Virtual) Tempe, Arizona, USA, 2022.
    [paper][codes]

2020

  1. Efficient Community Search over Large Directed Graph: An Augmented Index-based Approach
    Yankai Chen, Jie Zhang, Yixiang Fang, Xin Cao, Irwin King
    In Proceeding of the 29th International Joint Conferences on Artificial Intelligence (IJCAI), (Virtual) Yokohama, Japan, USA, 2020.
    [paper][full version][codes]

  2. A Literature Review of Recent Graph Embedding Techniques for Biomedical Data
    Yankai Chen, Yaozu Wu, Shicheng Ma, Irwin King.
    In Proceeding of the 27th international Conference on Neural Information Processing (ICONIP), Invited Paper, (Virtual) Bangkok, Thailand, 2020.
    [paper]

2019 and Before

  1. Exploring Communities in Large Profiled Graphs (Extended abstract)
    Yankai Chen, Yixiang Fang, Reynold Cheng, Yun Li, Xiangjun Chen, Jie Zhang
    In Proceeding of the 35th IEEE International Conference on Data Engineering (ICDE), Macau, China, 2019.
    [paper]

  2. Exploring Communities in Large Profiled Graphs
    Yankai Chen, Yixiang Fang, Reynold Cheng, Yun Li, Xiangjun Chen, Jie Zhang
    In Journal of IEEE Transactions on Knowledge & Data Engineering (TKDE), 2019.
    [paper] [full version][codes]

  3. Effective and Efficient Attributed Community Search
    Yixiang Fang, Reynold Cheng, Yankai Chen, Siqiang Luo, Jiafeng Hu
    In Journal of Journal on Very Large Data Bases (VLDBJ), 2017.
    [paper][codes]

Preprints

  1. Recent Advances of Multimodal Continual Learning: A Comprehensive Survey
    Dianzhi Yu, Xinni Zhang, Yankai Chen, Aiwei Liu, Yifei Zhang, Philip S Yu, Irwin King
    [arXiv]

  2. Knowledge-aware Neural Networks with Personalized Feature Referencing for Cold-start Recommendation
    Xinni Zhang, Yankai Chen, Cuiyun Gao, Qing Liao, Shenglin Zhao, Irwin King
    [arXiv][codes]

  3. Towards low-loss 1-bit quantization of user-item representations for top-k recommendation
    Yankai Chen, Yifei Zhang, Yingxue Zhang, Huifeng Guo, Jingjie Li, Ruiming Tang, Xiuqiang He, Irwin King
    [arXiv]

Ph.D. Dissertation