Publications

Sorted by Research Topics

Causal Discovery under the Practical Issues

• Conditional Independent Component Analysis for Estimating Causal Structure with Latent Variables.
  Yewei Xia, Zhengming Chen, Haoyue Dai, Fuhong Wang, Yixin Ren, Yiqing Li, Kun Zhang, Shuigeng Zhou.
  14th International Conference on Learning Representations (ICLR 2026)

• Causal Discovery by Multi-Level Wavelet Mapping Correlation Based Statistical Dependence Measurement.
  Yixin Ren, Hao Zhang, Yewei Xia, Feng Xie, Jihong Guan, Shuigeng Zhou.
  ACM Transactions on Knowledge Discovery from Data (TKDD)

• Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations
  Zhengming Chen, Yewei Xia, Feng Xie, Jie Qiao, Zhifeng Hao, Ruichu Cai, Kun Zhang.
  42nd International Conference on Machine Learning (ICML 2025)

• Identifying Causal Mechanism Shifts under Additive Models with Arbitrary Noise
  Yewei Xia*, Xueliang Cui*, Hao Zhang, Yixin Ren, Feng Xie, Jihong Guan, Ruxin Wang, Shuigeng Zhou.
  34th International Joint Conference on Artificial Intelligence (IJCAI 2025) [Python Code]

• Efficient Constraint-based Window Causal Graph Discovery in Time Series with Multiple Time Lags
  Yewei Xia, Yixin Ren, Hong Cheng, Hao Zhang, Jihong Guan, Minchuan Xu, Shuigeng Zhou.
  34th International Joint Conference on Artificial Intelligence (IJCAI 2025)

• Fast Causal Discovery by Approximate Kernel-based Generalized Score Functions with Linear Computational Complexity.
  Yixin Ren*, Haocheng Zhang*, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou.
  31st SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025 Research Track August)

• Towards Effective Causal Partitioning by Edge Cutting of Adjoint Graph.
  Hao Zhang*, Yixin Ren, Yewei Xia*, Shuigeng Zhou, Jihong Guan.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)

• Causal Discovery by Continuous Optimization with Conditional Independence Constraint: Methodology and Performance.
  Yewei Xia, Hao Zhang, Yixin Ren, Jihong Guan, and Shuigeng Zhou.
  23rd IEEE International Conference on Data Mining (ICDM 2023, regular paper, acceptance rate $\sim$ 9.37%)

• Differentially Private Nonlinear Causal Discovery from Numerical Data.
  Hao Zhang, Yewei Xia, Yixin Ren, Jihong Guan, Shuigeng Zhou.
  37th AAAI Conference on Artificial Intelligence (AAAI 2023)

Statistical (Conditional) Independence Test

• Independence Test for Linear Non-Gaussian Data and Applications in Causal Discovery.
  Yiqing Li, Xiaofei Wang, Boyang Sun, Yewei Xia, Kun Zhang.
  14th International Conference on Learning Representations (ICLR 2026).

• Regression-based Conditional Independence Test with Adaptive Kernels.
  Yixin Ren*, Juncai Zhang*, Yewei Xia, Ruxin Wang, Feng Xie, Hao Zhang, Shuigeng Zhou.
  Artificial Intelligence (AI)

• Score-based Generative Modeling for Conditional Independence Testing.
  Yixin Ren*, Chenghou Jin*, Yewei Xia, Li Ke, Longtao Huang, Hui Xue, Hao Zhang, Jihong Guan, Shuigeng Zhou.
  31st SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025 Research Track February)

• Extracting Rare Dependence Patterns via Adaptive Sample Reweighting.
  Yiqing Li*, Yewei Xia*, Xiaofei Wang, Zhengming Chen, Liuhua Peng, Mingming Gong, Kun Zhang.
  42nd International Conference on Machine Learning (ICML 2025)

• Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing.
  Yixin Ren, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou.
  38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024)

• Learning Adaptive Kernels for Statistical Independence Tests.
  Yixin Ren, Yewei Xia, Hao Zhang, Jihong Guan, Shuigeng Zhou.
  27th International Conference on Artificial Intelligence and Statistics (AISTATS 2024)

• Conditional Independence Test Based on Residual Similarity.
  Hao Zhang*, Yewei Xia*, Kun Zhang, Shuigeng Zhou, Jihong Guan.
  ACM Transactions on Knowledge Discovery from Data (TKDD)

• Multi-level Wavelet Mapping Correlation for Statistical Dependence Measurement: Methodology and Performance.
  Yixin Ren, Hao Zhang, Yewei Xia, Jihong Guan, Shuigeng Zhou.
  37th AAAI Conference on Artificial Intelligence (AAAI 2023)

Deep Learning (Continual Learning, Multi-modal Recommendation, Federated Learning)

• A New Model for Prototype-based Continual Learning in Hyperspherical Space.
  Yixin Ren, Yewei Xia, Li Ke, Longtao Huang, Hui Xue, Shuigeng Zhou.
  2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2025)

• Invariance Learning for Counterfactual Watch-time Prediction in Short Video Recommendation.
  Chenghou Jin*, Yixin Ren*, Hongxu Ma*, Yewei Xia, Yi Guan, Hao Zhang, Jiandong Ding, Jihong Guan, Shuigeng Zhou.
  40th AAAI Conference on Artificial Intelligence (AAAI 2026)

• Self-supervised Learning for Multimedia Recommendation.
  Zhulin Tao, Xiaohao Liu, Yewei Xia, Xiang Wang, Lifang Yang, Xianglin Huang, Tat-Seng Chua.
  IEEE Transactions on Multimedia (TMM)

• Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings.
  Yuxi Mi, Hongquan Liu, Yewei Xia, Yiheng Sun, Yateng Tang, Jihong Guan, Shuigeng Zhou.
  IEEE Transactions on Artificial Intelligence (TAI)

Discover Causal Knowledge in Biological Data

• Hybrid Causal Feature Selection for Cancer Biomarker Identification from RNA-seq Data.
  Wenwei Xu*, Hao Zhang*, Yewei Xia, Yixin Ren, Jihong Guan, Shuigeng Zhou.
  IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)

• Causal Gene Identification Using Non-linear Regression-based Independence Tests.
  Hao Zhang, Chuanxu Yan, Yewei Xia, Jihong Guan, Shuigeng Zhou.
  IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)