Publications

I'm interested in artificial intelligence (e.g. reinforcement Learning, federated Learning, sparse learning) and its applications.

Conference Papers:

• First Author Papers (Equal contribution*):

  1. Universal Domain Adaptation via Compressive Attention Matching
     Didi Zhu*, Yinchuan Li*, Junkun Yuan, Zexi Li, Kun Kuang, Chao Wu
     International Conference on Computer Vision (ICCV 2023) | paper

  2. Generative Flow Networks for Precise Reward-Oriented Active Learning on Graphs
     Yinchuan Li, Zhigang Li, Wenqian Li, Yunfeng Shao, Yan Zheng, Jianye Hao
     International Joint Conference on Artificial Intelligence, IJCAI 2023 | paper

  3. GFlowNets with Human Feedback
     Yinchuan Li, Shuang Luo, Yunfeng Shao, HAO Jianye
     International Conference on Learning Representations (ICLR), 2023 | paper

  4. Large Sparse Kernels for Federated Learning
     Feilong Zhang*, Yinchuan Li*, Shiyi Lin, Junjun Jiang, Xianming Liu
     International Conference on Learning Representations (ICLR) , 2023 | paper

  5. CFlowNets: Continuous Control with Generative Flow Networks
     Yinchuan Li, Shuang Luo, Haozhi Wang, Jianye Hao
     International Conference on Learning Representations (ICLR) , 2023 | paper

  6. DAG Matters! GFlowNets Enhanced Explainer For Graph Neural Networks
     Wenqian Li*, Yinchuan Li*, Zhigang Li, Jianye Hao, Yan Pang
     International Conference on Learning Representations (ICLR) , 2023 | paper

  7. Personalized Federated Learning via Variational Bayesian Inference
     Xu Zhang*, Yinchuan Li*, Wenpeng Li, Kaiyang Guo, Yunfeng Shao
     International Conference on Machine Learning (ICML), 2022 | paper

  8. S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
     Shuang Luo*, Yinchuan Li*, Jiahui Li, Kun Kuang, Furui Liu, Yunfeng Shao, Chao Wu
     SIGKDD, 2022 | paper

  9. Unfolded Deep Neural Network (UDNN) for High Mobility Channel Estimation
     Yinchuan Li, Xiaodong Wang, Robert L Olesen
     IEEE Wireless Communications and Networking Conference (WCNC) , 2021 | paper

  10. Optimistic Bull or Pessimistic Bear: Adaptive Deep Reinforcement Learning for Stock Portfolio Allocation
      Xinyi Li*, Yinchuan Li*, Yuancheng Zhan, Xiao-Yang Liu
      ICML Workshop on AI in Finance, 2019 | paper

  11. Compressive Multidimensional Harmonic Retrieval with Prior Knowledge
      Yinchuan Li, Xu Zhang, Zegang Ding, Xiaodong Wang
      IEEE International Conference on Signal, Information and Data Processing, 2019 | paper

  12. Risk management via anomaly circumvent: Mnemonic deep learning for midterm stock prediction
      Xinyi Li*, Yinchuan Li*, Xiao-Yang Liu, Christina Dan Wang
      SIGKDD Workshop on Anomaly Detection in Finance , 2019 | paper

• Corresponding Author Papers (Corresponding Author†):

  1. One Important Thing To Do Before Federated Training
     Yichu Xu*, Wenqian Li*,Yinchuan Li†, Yan Pang, De-Chuan Zhan
     International Conference on Learning Representations (ICLR) , 2023 | paper

  2. Regularized Offline GFlowNets
     Haozhi Wang, Yunfeng Shao, HAO Jianye, Yinchuan Li†
     International Conference on Learning Representations (ICLR) , 2023 | paper

  3. DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News
     Xinyi Li, Yinchuan Li†, Hongyang Yang, Liuqing Yang, Xiao-Yang Liu
     NeurIPS Workshop on Robust AI in Financial Services , 2019 | paper

• Others:

  1. Federated Learning with Position-Aware Neurons
     Xinchun Li, Yichu Xu, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Dechuan Zhan
     CVPR, 2022 | paper

  2. Avoid Overfitting User Specific Information in Federated Keyword Spotting
     Xinchun Li, Jin-Lin Tang, Shaoming Song, Bingshuai Li, Yinchuan Li, Yunfeng Shao, Le Gan, Dechuan Zhan
     Interspeech, 2022 | paper

  3. Communication Reducing Quantization for Federated Learning with Local Differential Privacy Mechanism
     Huixuan Zong, Qing Wang, Xiaofeng Liu, Yinchuan Li, Yunfeng Shao
     IEEE/CIC International Conference on Communications in China (ICCC), 2021 | paper

  4. Price prediction of cryptocurrency: an empirical study
     Liuqing Yang, Xiao-Yang Liu, Xinyi Li, Yinchuan Li
     International Conference on Smart Blockchain , 2019 | paper

  5. Asymmetric Temperature Scaling Makes Larger Networks Teach Well Again
     Xin-Chun Li, Wen-Shu Fan, Shaoming Song, Yinchuan Li, Bingshuai Li, Yunfeng Shao, De-Chuan Zhan
     NeurIPS, 2022 | paper

Journal Papers:

• First Author Papers (Equal contribution*):

  1. Interference Removal for Radar/Communication Co-existence: the Random Scattering Case
     Yinchuan Li, Le Zheng, Marco Lops, Xiaodong Wang
     IEEE Transactions on Wireless Communications, July, 2019 | paper

  2. Spectrum Recovery for Clutter Removal in Penetrating Radar Imaging
     Yinchuan Li, Xiaodong Wang, Zegang Ding, et al.
     IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 9, pp. 6650-6665, Sept. 2019 | paper

  3. Multidimensional Spectral Super-Resolution With Prior Knowledge With Application to High Mobility Channel Estimation
     Yinchuan Li, Xiaodong Wang, Zegang Ding
     IEEE Journal on Selected Areas in Communications,2019 | paper

  4. Multi-target position and velocity estimation using OFDM communication signals
     Yinchuan Li, Xiaodong Wang, Zegang Ding,
     IEEE Transactions on Communications,2019 | paper

  5. Sparse Personalized Federated Learning
     Xiaofeng Liu*, Yinchuan Li*, Qing Wang, Xu Zhang, Yunfeng Shao, Yanhui Geng.
     IEEE Transactions on Neural Networks and Learning Systems, 2020 | paper

  6. Three-dimensional optimal focusing imaging algorithm for wall-penetrating radar
     Yinchuan Li, Yikun Zhao, Yin Xiang, Zegang Ding, Haibo Liu, Quanhua Liu
     The Journal of Engineering ,2019 | paper

• Corresponding Author Papers (Corresponding Author†):

  1. ADMM-Net for Communication Interference Removal in Stepped-Frequency Radar
     Jeremy Johnston, Yinchuan Li†, Marco Lops, Xiaodong Wang
     IEEE Transactions on Signal Processing, 2021 | paper

  2. Parametric translational compensation for ISAR imaging based on cascaded subaperture integration with application to asteroid imaging
     Zegang Ding, Siyuan Liu, Yinchuan Li†, Pengjie You, Xu Zhou
     IEEE Transactions on Geoscience and Remote Sensing ,2020 | paper

• Others:

  1. Near-Field Autofocusing Imaging and Parameter Estimation for Penetrating Radar
     Zegang Ding, Yinchuan Li, Wei Liu, et al.
     IEEE Transactions on Geoscience and Remote Sensing, Aug. 2019 | paper

  2. SAR parametric super-resolution image reconstruction methods based on ADMM and deep neural network
     Yangkai Wei, Yinchuan Li, Zegang Ding, Yan Wang, Tao Zeng, Teng Long
     IEEE Transactions on Geoscience and Remote Sensing, 2020 | paper

  3. Multi-angle SAR Sparse Imaging with Improved Attributed Scattering Model
     Yangkai Wei, Yinchuan Li, Xinliang Chen, Zegang Ding
     IEEE Geoscience and Remote Sensing Letters, 2019. | paper

  4. Multi-path Suppression Algorithm For Through-the-wall Imaging
     Yikun Zhao, Wenfu Yang, Yinchuan Li, et al.
     IET The Journal of Engineering, 2019. | paper

  5. Towards Effective Clustered Federated Learning: A Peer-to-peer Framework with Adaptive Neighbor Matching
     Zexi Li, Jiaxun Lu, Shuang Luo, Didi Zhu, Yunfeng Shao, Yinchuan Li, Zhimeng Zhang, Yongheng Wang, Chao Wu.
     IEEE Transactions on Big Data. | paper

Preprints:

• First Author Papers (Equal contribution*):

  1. Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance
     Didi Zhu*, Yinchuan Li*, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu
     arXiv preprint 2023 | paper

  2. Generalized Universal Domain Adaptation with Generative Flow Networks
     Didi Zhu*, Yinchuan Li*, Yunfeng Shao, Jianye Hao, Fei Wu, Kun Kuang, Jun Xiao, Chao Wu,
     arXiv preprint 2023 | paper

  3. Multi-agent Policy Reciprocity with Theoretical Guarantee
     Haozhi Wang*, Yinchuan Li*, Qing Wang, Yunfeng Shao, Jianye Hao
     arXiv preprint 2023 | paper

  4. Generative Multi-Flow Networks: Centralized, Independent and Conservation
     Yinchuan Li*, Haozhi Wang, Shuang Luo, HAO Jianye,
     2022 | paper

  5. Structured Directional Pruning via Perturbation Orthogonal Projection
     Xiaofeng Liu*, Yinchuan Li*, Yunfeng Shao, Qing Wang, Yanhui Geng
     arXiv preprint 2021 | paper

  6. Sparse Federated Learning with Hierarchical Personalization Models
     Xiaofeng Liu, Yinchuan Li*, Yunfeng Shao, Qing Wang,
     arXiv preprint 2022 | paper

• Corresponding Author Papers (Corresponding Author†):

  1. Meta Generative Flow Networks with Personalization for Task-Specific Adaptation
     Xinyuan Ji, Xu Zhang, Wei Xi, Haozhi Wang, Olga Gadyatskaya, Yinchuan Li†
     arXiv preprint 2023 | paper

  2. Federated Learning via Variational Bayesian Inference: Personalization, Sparsity and Clustering
     Xinyuan Ji, Xu Zhang, Wei Xi, Haozhi Wang, Olga Gadyatskaya, Yinchuan Li†
     arXiv preprint 2023 | paper

  3. GFlowCausal: Generative Flow Networks for Causal Discovery
     Wenqian Li, Yinchuan Li†, Shengyu Zhu, Yunfeng Shao, Jianye Hao, Yan Pang
     arXiv preprint 2022 | paper

  4. On the Convergence Theory of Meta Reinforcement Learning with Personalized Policies
     Haozhi Wang, Qing Wang, Yunfeng Shao, Dong Li, Jianye Hao, Yinchuan Li†
     arXiv preprint 2022 | paper

  5. Tensor Decomposition based Personalized Federated Learning
     Qing Wang, Jing Jin, Xiaofeng Liu, Huixuan Zong, Yunfeng Shao, Yinchuan Li†
     arXiv preprint 2022 | paper