Linglong Kong

Venues

Frequent coauthors

Papers

1. Adaptive Conformal Prediction Intervals for Invariant Learning
   SIGKDD 2025 ·

   Shuxin Liang

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2. Advancing Fairness in Precision Medicine: A Universal Framework for Optimal Treatment Estimation in Censored Data
   AISTATS 2025 ·

   Hongni Wang

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3. CBMA: Improving Conformal Prediction through Bayesian Model Averaging
   ICLR 2025 ·

   Pankaj Bhagwat

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4. Differentially Private Analysis for Binary Response Models: Optimality, Estimation, and Inference
   ICML 2025 ·

   Ce Zhang

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5. Intrinsic Benefits of Categorical Distributional Loss: Uncertainty-aware Regularized Exploration in Reinforcement Learning
   NeurIPS 2025 ·

   Ke Sun

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6. Oblivious Johnson-Lindenstrauss embeddings for compressed Tucker decompositions
   CIKM 2025 ·

   Matthew Pietrosanu

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7. Understanding Fairness and Prediction Error through Subspace Decomposition and Influence Analysis
   NeurIPS 2025 ·

   Enze Shi

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8. A Bayesian Hierarchical Model for Orthogonal Tucker Decomposition with Oblivious Tensor Compression
   ICDM 2024 ·

   Matthew Pietrosanu

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9. Analysis of Differentially Private Synthetic Data: A Measurement Error Approach
   AAAI 2024 ·

   Yangdi Jiang

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10. Debiasing with Sufficient Projection: A General Theoretical Framework for Vector Representations
    NAACL 2024 ·

    Enze Shi

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11. Distributional Reinforcement Learning with Regularized Wasserstein Loss
    NeurIPS 2024 ·

    Ke Sun

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12. Probing Social Bias in Labor Market Text Generation by ChatGPT: A Masked Language Model Approach
    NeurIPS 2024 ·

    Lei Ding

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13. Responsible Bandit Learning via Privacy-Protected Mean-Volatility Utility
    AAAI 2024 ·

    Shanshan Zhao

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14. Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data
    ICML 2024 ·

    Yafei Wang

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15. Tuning-free Estimation and Inference of Cumulative Distribution Function under Local Differential Privacy
    ICML 2024 ·

    Yi Liu

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