Selected Publications:

Learning Theory

• All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
  Jasper C.H. Lee, Walter McKelvie, Maoyuan Song, Paul Valiant
  ICML 2025 (Oral presentation).
  


• Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation
  Ilias Diakonikolas, Daniel M. Kane, Jasper C.H. Lee, Thanasis Pittas
  SODA 2025.
  [arXiv]


• Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond 1+α Moments
  Trung Dang, Jasper C.H. Lee, Maoyuan Song and Paul Valiant
  NeurIPS 2023.
  [arXiv]


• Finite-Sample Symmetric Mean Estimation with Fisher Information Rate
  Shivam Gupta, Jasper C.H. Lee and Eric Price
  COLT 2023.
  [arXiv]


• Optimal Sub-Gaussian Mean Estimation in Very High Dimensions
  Jasper C.H. Lee and Paul Valiant
  ITCS 2022, pages 98:1-98:21.
  [Proceedings]


• Optimal Sub-Gaussian Mean Estimation in R
  Jasper C.H. Lee and Paul Valiant
  FOCS 2021, pages 672-683.
  [arXiv] [Proceedings]

Machine Learning for Optimization under Uncertainty

• Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs
  Xinyi Hu, Jasper C.H. Lee, Jimmy H.M. Lee, Peter J. Stuckey
  NeurIPS 2024.
  


• Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints
  Xinyi Hu, Jasper C.H. Lee and Jimmy H.M. Lee
  NeurIPS 2023.
  [arXiv]


• Predict+Optimize for Packing and Covering LPs with Unknown Parameters in Constraints
  Xinyi Hu, Jasper C.H. Lee and Jimmy H.M. Lee
  AAAI 2023. (Oral presentation)
  [arXiv]

All Publications:

1. All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
   Jasper C.H. Lee, Walter McKelvie, Maoyuan Song, Paul Valiant
   ICML 2025 (Oral presentation).
   


2. On Learning Parallel Pancakes with Mostly Uniform Weights
   Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar, Jasper C.H. Lee, Thanasis Pittas
   ICML 2025 (Spotlight).
   


3. On Fine-Grained Distinct Element Estimation
   Ilias Diakonikolas, Daniel Kane, Jasper C.H. Lee, Thanasis Pittas, David Woodruff, Samson Zhou
   ICML 2025.
   


4. Clustering Mixtures of Bounded Covariance Distributions Under Optimal Separation
   Ilias Diakonikolas, Daniel M. Kane, Jasper C.H. Lee, Thanasis Pittas
   SODA 2025.
   [arXiv]


5. Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs
   Xinyi Hu, Jasper C.H. Lee, Jimmy H.M. Lee, Peter J. Stuckey
   NeurIPS 2024.
   


6. Minimax-Optimal Location Estimation
   Shivam Gupta, Jasper C.H. Lee, Eric Price and Paul Valiant
   NeurIPS 2023.
   


7. Optimality in Mean Estimation: Beyond Worst-Case, Beyond Sub-Gaussian, and Beyond 1+α Moments
   Trung Dang, Jasper C.H. Lee, Maoyuan Song and Paul Valiant
   NeurIPS 2023.
   [arXiv]


8. A Spectral Algorithm for List-Decodable Covariance Estimation in Relative Frobenius Norm
   Ilias Diakonikolas, Daniel Kane, Jasper C.H. Lee, Ankit Pensia and Thanasis Pittas
   NeurIPS 2023 (Spotlight).
   [arXiv]


9. Two-Stage Predict+Optimize for MILPs with Unknown Parameters in Constraints
   Xinyi Hu, Jasper C.H. Lee and Jimmy H.M. Lee
   NeurIPS 2023.
   [arXiv]


10. Finite-Sample Symmetric Mean Estimation with Fisher Information Rate
    Shivam Gupta, Jasper C.H. Lee and Eric Price
    COLT 2023.
    [arXiv]


11. High-dimensional Location Estimation via Norm Concentration for Subgamma Vectors
    Shivam Gupta, Jasper C.H. Lee and Eric Price
    ICML 2023.
    [arXiv]


12. Branch & Learn with Post-hoc Correction for Predict+Optimize with Unknown Parameters in Constraints
    Xinyi Hu, Jasper C.H. Lee and Jimmy H.M. Lee
    CPAIOR 2023.
    


13. Predict+Optimize for Packing and Covering LPs with Unknown Parameters in Constraints
    Xinyi Hu, Jasper C.H. Lee and Jimmy H.M. Lee
    AAAI 2023. (Oral presentation)
    [arXiv]


14. Finite-Sample Maximum Likelihood Estimation of Location
    Shivam Gupta, Jasper C.H. Lee, Eric Price and Paul Valiant
    NeurIPS 2022.
    [arXiv]


15. Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions
    Ilias Diakonikolas, Daniel Kane, Jasper C.H. Lee and Ankit Pensia
    NeurIPS 2022.
    [arXiv]


16. Branch & Learn for Recursively and Iteratively Solvable Problems in Predict+Optimize
    Xinyi Hu, Jasper C.H. Lee, Jimmy H.M. Lee and Allen Z. Zhong
    NeurIPS 2022.
    [arXiv]


17. Optimal Sub-Gaussian Mean Estimation in Very High Dimensions
    Jasper C.H. Lee and Paul Valiant
    ITCS 2022, pages 98:1-98:21.
    [Proceedings]


18. Optimal Sub-Gaussian Mean Estimation in R
    Jasper C.H. Lee and Paul Valiant
    FOCS 2021, pages 672-683.
    [arXiv] [Proceedings]


19. Finding the Mode of a Kernel Density Estimate
    Jasper C.H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips and Wai Ming Tai
    ESA 2021, pages 61:1-61:19.
    [arXiv] [Proceedings]


20. Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies
    ICML 2021, pages 1908-1919.
    Uthsav Chitra, Kimberly Ding, Jasper C.H. Lee and Benjamin Raphael
    [arXiv] [Proceedings]


21. Uncertainty about Uncertainty: Optimal Adaptive Algorithms for Estimating Mixtures of Unknown Coins
    SODA 2021, pages 394-413.
    Jasper C.H. Lee and Paul Valiant
    [arXiv] [Proceedings]


22. Fast Algorithms for Computing Interim Allocations in Single-Parameter Environments
    PRIMA 2018, pages 194-209.
    Amy Greenwald, Jasper Lee, Takehiro Oyakawa
    


23. Augmenting Stream Constraint Programming with Eventuality Conditions
    CP 2018, pages 242-258.
    Jasper C.H. Lee, Jimmy H.M. Lee and Zhuowei Zhong
    [arXiv] [Proceedings]


24. Optimizing Star-Convex Functions
    FOCS 2016, pages 603-614.
    Jasper C.H. Lee and Paul Valiant
    [arXiv] [Proceedings]


25. Towards Practical Infinite Data Stream Constraint Solving: Applications and Implementation
    CP 2014, pages 449-464.
    Jasper C.H. Lee and Jimmy H.M. Lee
    [Proceedings]