PPaperPicks

Bei Jiang

13 papers at tracked venues · 9 at CORE A* · active 2024–2025

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Venues

NeurIPS ×4AAAI ×2ICML ×2AISTATS ×1CIKM ×1ICDM ×1ICLR ×1NAACL ×1

Frequent coauthors

Linglong Kong
×13
Xiaodong Yan
×5
Enze Shi
×4
Yafei Wang
×3
Junxi Zhang
×2
Pankaj Bhagwat
×2
Ke Sun
×2
Yingnan Zhao
×2
Matthew Pietrosanu
×2
Lei Ding
×2
Hongni Wang
×1
Na Li
×1

Papers

  1. Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data
    AISTATS 2025 ·
    Hongni Wang
    ,
    Junxi Zhang
    ,
    Na Li
    ,
    Linglong Kong
    , Bei Jiang,
    Xiaodong Yan
  2. CBMA: Improving Conformal Prediction through Bayesian Model Averaging
    ICLR 2025 ·
    Pankaj Bhagwat
    ,
    Linglong Kong
    , Bei Jiang
  3. Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
    ICML 2025 ·
    Ce Zhang
    ,
    Yixin Han
    ,
    Yafei Wang
    ,
    Xiaodong Yan
    ,
    Linglong Kong
    ,
    Ting Li
    , Bei Jiang
  4. Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning
    NeurIPS 2025 ·
    Ke Sun
    ,
    Yingnan Zhao
    ,
    Enze Shi
    ,
    Yafei Wang
    ,
    Xiaodong Yan
    , Bei Jiang,
    Linglong Kong
  5. Oblivious Johnson-Lindenstrauss embeddings for compressed Tucker decompositions
    CIKM 2025 ·
    Matthew Pietrosanu
    , Bei Jiang,
    Linglong Kong
  6. Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis
    NeurIPS 2025 ·
    Enze Shi
    ,
    Pankaj Bhagwat
    ,
    Zhixian Yang
    ,
    Linglong Kong
    , Bei Jiang
  7. A Bayesian Hierarchical Model for Orthogonal Tucker Decomposition with Oblivious Tensor Compression
    ICDM 2024 ·
    Matthew Pietrosanu
    , Bei Jiang,
    Linglong Kong
  8. Analysis of Differentially Private Synthetic Data: A Measurement Error Approach
    AAAI 2024 ·
    Yangdi Jiang
    ,
    Yi Liu
    ,
    Xiaodong Yan
    ,
    Anne-Sophie Charest
    ,
    Linglong Kong
    , Bei Jiang
  9. Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations
    NAACL 2024 ·
    Enze Shi
    ,
    Lei Ding
    ,
    Linglong Kong
    , Bei Jiang
  10. Distributional Reinforcement Learning with Regularized Wasserstein Loss
    NeurIPS 2024 ·
    Ke Sun
    ,
    Yingnan Zhao
    ,
    Wulong Liu
    , Bei Jiang,
    Linglong Kong
  11. Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach
    NeurIPS 2024 ·
    Lei Ding
    ,
    Yang Hu
    ,
    Nicole Denier
    ,
    Enze Shi
    ,
    Junxi Zhang
    ,
    Qirui Hu
    ,
    Karen D. Hughes
    ,
    Linglong Kong
    , Bei Jiang
  12. Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility
    AAAI 2024 ·
    Shanshan Zhao
    ,
    Wenhai Cui
    , Bei Jiang,
    Linglong Kong
    ,
    Xiaodong Yan
  13. Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data
    ICML 2024 ·
    Yafei Wang
    ,
    Bo Pan
    ,
    Mei Li
    ,
    Jianya Lu
    ,
    Lingchen Kong
    , Bei Jiang,
    Linglong Kong