Shimin DI

Selected Interesting Pre-prints and Papers

FULL PUBLICATION LIST

  • Shimin DI, Quanming YAO, Yongqi ZHANG*, Xiaofang ZHOU, Lei CHEN. "Efficient Latent-based Scoring Function Search for N-ary Relational Knowledge Bases".
    ACM Transactions on Knowledge Discovery from Data (TKDD).
  • Yuchen LIU, Shimin DI*, Lei CHEN, Xiaofang ZHOU and Fei LIN "A Universal and Interpretable Method for Enhancing Stock Price Prediction".
    33rd ACM International Conference on Information and Knowledge Management (CIKM 2024).
  • Jiachuan WANG, Shimin DI*, Lei CHEN, Charles Wang-wai NG: "Learning from Emergence: A Study on Proactively Inhibiting the Monosemantic Neurons of Artificial Neural Networks".
    30TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2024).
  • Ran LI, Shimin DI*, Lei CHEN, Xiaofang ZHOU: "SimDiff: Simple Denoising Probabilistic Latent Diffusion Model for data augmentation on Multi-modal Knowledge Graph".
    30TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2024).
  • Haoyang LI, Shimin DI*, Calvin LI, Lei CHEN, Xiaofang ZHOU: "Fight Fire with Fire: Towards Robust Graph Neural Networks on Dynamic Graphs via Actively Defense".
    50TH International Conference on Very Large Databases (VLDB 2024).
  • Ran LI, Shimin DI*, Lei CHEN, Xiaofang ZHOU: "GradGCL: Gradient Graph Contrastive Learning".
    40TH IEEE International Conference on Data Engineering (ICDE 2024).
  • Zhili WANG, Shimin DI*, Lei CHEN, Xiaofang ZHOU: "Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks".
    40TH IEEE International Conference on Data Engineering (ICDE 2024).
  • Haoyang LI, Shimin DI*, Lei CHEN, Xiaofang ZHOU: "E2GCL: Efficient and Expressive Contrastive Learning on Graph Neural Networks".
    40TH IEEE International Conference on Data Engineering (ICDE 2024).
  • Hanmo LIU, Shimin DI*, Haoyang LI, Shuangyin LI, Lei CHEN, Xiaofang ZHOU: "Effective Data Selection and Replay for Unsupervised Continual Learning".
    40TH IEEE International Conference on Data Engineering (ICDE 2024).
  • Shimin DI, Lei CHEN*: "Message Function Search for Knowledge Graph Embedding".
    32TH Proceedings of the ACM Web Conference (WWW 2023).
  • Jiachuan WANG, Shimin DI*, Lei CHEN, Charles Wang Wai NG: "Noise2Info: Noisy Image to Information of Noise for Self-Supervised Image Denoising".
    Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV 2023).
  • Zhili WANG, Shimin DI*, Lei CHEN: "A Message Passing Neural Network Space for Better Capturing Data-dependent Receptive Fields".
    29TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2023).
  • Hanmo LIU, Shimin DI*, Lei CHEN: "Incremental Tabular Learning on Heterogeneous Feature Space".
    Proceedings of the ACM on Management of Data (SIGMOD 2023).
  • Haoyang LI, Shimin DI*, Lei CHEN: "Revisiting Injective Attacks on Recommender Systems".
    36TH Advances in Neural Information Processing Systems (NeurIPS 2022).
  • Haoyang LI, Shimin DI*, Zijian LI, Lei CHEN, Jiannong CAO: "Black-box Adversarial Attack and Defense on Graph Neural Networks".
    IEEE 38th International Conference on Data Engineering (ICDE 2022).
  • Shimin DI, Quanming YAO, Lei CHEN: "Searching to Sparsify Tensor Decomposition for N-ary Relational Data".
    30TH Proceedings of the ACM Web Conference (WWW 2021).
  • Shimin DI, Yongqi ZHANG, Quanming YAO*, Lei CHEN: "Efficient Relation-aware Scoring Function Search for Knowledge Graph Embedding".
    IEEE 37th International Conference on Data Engineering (ICDE 2021).
  • Zhili WANG, Shimin DI*, Lei CHEN: "AutoGEL: An Automated Graph Neural Network with Explicit Link Information".
    35TH Advances in Neural Information Processing Systems (NeurIPS 2021).
  • Jia LI, Shimin DI, Yanyan SHEN*, Lei CHEN: "FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection".
    14TH ACM International Conference on Web Search and Data Mining (WSDM 2021).
  • Shimin DI, Yanyan SHEN*, Lei CHEN: "Relation Extraction via Domain-aware Transfer Learning".
    25TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2019).
  • Shimin DI, Jingshu PENG, Yanyan SHEN*, Lei CHEN: "Transfer Learning via Feature Isomorphism Discovery".
    24TH ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2018).