Publications


★: student co-authors

Manuscripts (on open-access archives)

  • J. Dong★, R. K. W. Wong and K. C. G. Chan. (2024) "Balancing Method for Non-monotone Missing Data".
    [abstract] [arXiv]
  • S. Hong★, Z. Qi and R. K. W. Wong. (2024) "Distributional Off-policy Evaluation with Bellman Residual Minimization".
    [abstract] [arXiv]
  • H. You, J. Wang, R. K. W. Wong, C. Schumacher, R. Saravanan and M. Jun. (2023) "Prediction of Tropical Pacific Rain Rates with Over-parameterized Neural Networks".
    [abstract] [arXiv]
  • J. Wang★, R. K. W. Wong, X. Zhang and K. C. G. Chan. (2023) "Flexible Functional Treatment Effect Estimation".
    [abstract] [arXiv]

Refereed Papers

2024

  • Y. Zhou★, R. K. W. Wong and K. He. (2024+) "Broadcasted Nonparametric Tensor Regression". Journal of the Royal Statistical Society: Series B.
    [abstract] [arXiv] [code]
  • F. Zhang★, Y. Zhou★, K. He and R. K. W. Wong. (2024+) "Multivariate Varying-coefficient Models via Tensor Decomposition". Statistica Sinica.
    [abstract] [journal]
  • W. Xue★, X. Zhang, K. C. G. Chan and R. K. W. Wong. (2024) "RKHS-based Covariate Balancing for Survival Causal Effect Estimation". Lifetime Data Analysis, 30, 34-58.
    [abstract] [journal] [code]
  • R. K. W. Wong. (2024) "Handbook of Matching and Weighting Adjustments for Causal Inference by José R. Zubizarreta, Elizabeth A. Stuart, Dylan S. Small, and Paul R. Rosenbaum". Journal of the American Statistical Association, 119(545), 791-791.
    [abstract] [journal]

2023

  • S. Yi, R. K. W. Wong and I. Gaynanova. (2023) "Hierarchical Nuclear Norm Penalization for Multi-view Data". Biometrics, 79, 2933-2946.
    [abstract] [journal] [arXiv] [code]
  • J. Wang★, Z. Qi and R. K. W. Wong. (2023) "Projected State-action Balancing Weights for Offline Reinforcement Learning". The Annals of Statistics, 51(4), 1639-1665.
    [abstract] [journal] [arXiv]
  • S. Roy★, R. K. W. Wong and Y. Ni. (2023) "Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data". Advances in Neural Information Processing Systems (NeurIPS).
    NeurIPS Scholar Award (S. Roy)
    [abstract] [arXiv]
  • S. Chen★, K. He, S. He, Y. Ni and R. K. W. Wong. (2023) "Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior". Technometrics, 65(4):524-536.
    [abstract] [journal] [arXiv]
  • R. Miao★, X. Zhang and R. K. W. Wong. (2023) "A Wavelet-Based Independence Test for Functional Data with an Application to MEG Functional Connectivity". Journal of the American Statistical Association, 118(543), 1876-1889.
    ICSA Student Paper Award (R. Miao)
    [abstract] [journal] [arXiv] [code]
  • J. Li★, T. V. Nguyen, C. Hegde and R. K. W. Wong. (2023) "Implicit Regularization for Group Sparsity". International Conference on Learning Representations (ICLR).
    [abstract] [arXiv] [code]
  • A. Adak★, M. Kang★, S. L. Anderson★, S. Murray, D. Jarquin, R. K. W. Wong and M. Katzfuss. (2023) "Phenomic Data-driven Biological Prediction of Maize through Field-based High Throughput Phenotyping Integration with Genomic Data". Journal of Experimental Botany, 74(17), 5307-5326.
    [abstract] [journal]

2022

  • J. Wang★, R. K. W. Wong, S. Yang and K. C. G. Chan. (2022) "Estimation of Partially Conditional Average Treatment Effect by Double Kernel-covariate Balancing". Electronic Journal of Statistics 16(2), 4332-4378.
    [abstract] [journal] [arXiv] [code]
  • J. Wang★, R. K. W. Wong and X. Zhang. (2022) "Low-Rank Covariance Function Estimation for Multidimensional Functional Data". Journal of the American Statistical Association, 117(538), 809-822.
    ASA Section on Nonparametric Statistics Student Paper Award (J. Wang)
    [abstract] [journal] [arXiv] [code]
  • Z. Wei★, R. K. W. Wong and T. C. M. Lee. (2022) "Extending the Use of MDL for High-Dimensional Problems: Variable Selection, Robust Fitting, and Additive Modeling". IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
    [abstract] [proceedings] [arXiv]
  • M. M. Meskhi★, N. E. Wolfe★, Z. Dai★, C. Frohlich, J. M. Miller, R. K. W. Wong and R. Vilalta. (2022) "A New Constraint on the Nuclear Equation of State from Statistical Distributions of Compact Remnants of Supernovae". Astrophysical Journal Letters 932(1), L3.
    [abstract] [journal] [arXiv] [code]
  • M. E. Lockhart★, O.-M. Kwok, M. Yoon and R. K. W. Wong. (2022) "An important component to investigating STEM persistence: the development and validation of the science identity (SciID) scale". International Journal of STEM Education, 9(1), 34.
    [abstract] [journal]

2021

  • J. Li★, T. V. Nguyen, C. Hegde and R. K. W. Wong. (2021) "Implicit Sparse Regularization: The Impact of Depth and Early Stopping". Advances in Neural Information Processing Systems (NeurIPS).
    [abstract] [proceedings] [arXiv] [code]
  • X. Mao★, R. K. W. Wong and S. X. Chen. (2021) "Matrix Completion under Low-Rank Missing Mechanism". Statistica Sinica, 31(4), 2005-2030.
    [abstract] [journal] [arXiv]
  • J. Wang★, R. K. W. Wong, X. Mao and K. C. G. Chan. (2021) "Matrix Completion with Model-free Weighting". International Conference on Machine Learning (ICML).
    [abstract] [proceedings] [arXiv] [code]
  • T. V. Nguyen★, R. K. W. Wong and C. Hegde. (2021) "Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis". IEEE Transactions on Information Theory, 67(7), 4669-4692.
    [abstract] [journal] [arXiv]
  • Y. Zhou★, R. K. W. Wong and K. He. (2021) "Tensor Linear Regression: Degeneracy and Solution". IEEE Access, 9, 7775-7788.
    [abstract] [journal] [arXiv]
  • J. Wang★, R. K. W. Wong, M. Jun, C. Schumacher, R. Saravanan and C. Sun★. (2021) "Statistical and Machine Learning Methods Applied to the Prediction of Tropical Rainfall". Environmental Research Communications, 3(11), 111001.
    [abstract] [journal] [ESSOAr]
  • R. Woodruff★, N. Beebe★, P. K. Josan★, P. Dutta★, R. K. W. Wong, B. Dunbar, D. Selva and A. Diaz-Artiles. (2021) "3D Interactive Model of HERA to Support ECLSS Anomaly Resolution Using a Virtual Assistant". IEEE Aerospace Conference.
    [abstract] [proceedings]
  • P. K. Josan★, P. Dutta★, R. Woodruff★, N. Beebe★, K. York★, O. Balcells-Quintana★, L. Kluis★, A. Viros★, B. Dunbar, R. K. W. Wong, D. Selva and A. Diaz-Artiles. (2021) "Experimental Design & Pilot Testing for ECLSS Anomaly Resolution using Daphne-AT Virtual Assistant". IEEE Aerospace Conference.
    [abstract] [proceedings]

2020

  • Y. Su★, R. K. W. Wong and T. C. M. Lee. (2020) "Network Estimation via Graphon with Node Features". IEEE Transactions on Network Sciences and Engineering, 7(3), 2078-2089.
    [abstract] [journal] [arXiv] [code]
  • X. Mao★, S. Dutta, R. K. W. Wong and D. Nettleton. (2020) "Adjusting for Spatial Effects in Genomic Prediction". Journal of Agricultural, Biological, and Environmental Statistics, 25(4), 699-718.
    [abstract] [journal] [arXiv]
  • W. Liu, X. Mao and R. K. W. Wong. (2020) "Median Matrix Completion: from Embarrassment to Optimality". International Conference on Machine Learning (ICML).
    [abstract] [proceedings] [arXiv]
  • I. Song★, I. H. Cho and R. K. W. Wong. (2020) "An Advanced Statistical Approach to Data-Driven Earthquake Engineering". Journal of Earthquake Engineering, 24(8), 1245-1269.
    [abstract] [journal]
  • P. Dutta★, O. Balcells-Quintana★, A. Viros★, R. Whittle★, P. K. Josan★, N. Beebe★, B. Dunbar, R. K. W. Wong, A. Diaz-Artiles and D. Selva. (2020) "Virtual Assistant for Anomaly Treatment in Long Duration Exploration Missions". AIAA SciTech Forum.
    [abstract] [proceedings]

2019

  • T. V. Nguyen★, R. K. W. Wong and C. Hegde. (2019) "Provably Accurate Double-Sparse Coding". Journal of Machine Learning Research, 20(141), 1-43.
    [abstract] [journal] [arXiv]
  • T. V. Nguyen★, R. K. W. Wong and C. Hegde. (2019) "On the Dynamics of Gradient Descent for Autoencoders". International Conference on Artificial Intelligence and Statistics (AISTATS).
    Earlier version 'Autoencoders Learn Generative Linear Models' appeared at ICML2018 workshop on Theoretical Foundations and Applications of Deep Generative Models
    [abstract] [proceedings] [arXiv]
  • R. K. W. Wong, Y. Li and Z. Zhu. (2019) "Partially Linear Functional Additive Models for Multivariate Functional Data". Journal of the American Statistical Association, 114(525), 406-418.
    [abstract] [journal] [supplement]
  • X. Mao★, S. X. Chen and R. K. W. Wong. (2019) "Matrix Completion with Covariate Information". Journal of the American Statistical Association, 114(525), 198-210.
    ICSA Student Paper Award (X. Mao)
    [abstract] [journal] [supplement]
  • J. Wang★, R. K. W. Wong and T. C. M. Lee. (2019) "Locally Linear Embedding with Additive Noise". Pattern Recognition Letters 123, 47-52.
    [abstract] [journal]
  • R. K. W. Wong and X. Zhang. (2019) "Nonparametric Operator-Regularized Covariance Function Estimation for Functional Data". Computational Statistics & Data Analysis, 131, Special Issue on High-dimensional and Functional Data Analysis, 131-144.
    [abstract] [journal] [arXiv] [supplement] [code]

2018

  • T. Nguyen★, R. K. W. Wong and C. Hegde. (2018) "A Provable Approach for Double-Sparse Coding". AAAI Conference on Artificial Intelligence (AAAI).
    Oral Presentation
    [abstract] [proceedings] [arXiv]

2017

  • R. K. W. Wong and T. C. M. Lee. (2017) "Matrix Completion with Noisy Entries and Outliers". Journal of Machine Learning Research, 18(147), 1-25.
    [abstract] [journal] [arXiv]
  • R. K. W. Wong, C. B. Storlie and T. C. M. Lee. (2017) "A Frequentist Approach to Computer Model Calibration". Journal of the Royal Statistical Society: Series B, 79(2), 635-648.
    [abstract] [journal] [arXiv] [supplement] [code]
  • Z. Liao★, G. T. Amariucai, R. K. W. Wong and Y. Guan. (2017) "The Impact of Discharge Inversion Effect on Learning SRAM Power-Up Statistics". IEEE Asian Hardware Oriented Security and Trust Symposium (AsianHOST).
    [abstract] [proceedings]

2016

  • R. K. W. Wong, T. C. M. Lee, D. Paul, J. Peng and for the Alzheimer's Disease Neuroimaging Initiative. (2016) "Fiber Direction Estimation, Smoothing and Tracking in Diffusion MRI". The Annals of Applied Statistics, 10(3), 1137-1156.
    Discussion Paper
    [abstract] [journal] [arXiv] [PDF] [supplement]
  • R. K. W. Wong, V. L. Kashyap, T. C. M. Lee and D. A. van Dyk. (2016) "Detecting Abrupt Changes in the Spectra of High-energy Astrophysical Sources". The Annals of Applied Statistics, 10(2), 1107-1134.
    [abstract] [journal] [arXiv] [PDF] [code]

2014

  • S. Han, R. K. W. Wong, T. C. M. Lee, L. Shen, S.-Y. R. Li and X. Fan. (2014) "A Full Bayesian Approach for Boolean Genetic Network Inference". PLoS ONE, 9(12):e115806.
    [abstract] [journal]
  • R. K. W. Wong, P. Baines, A. Aue, T. C. M. Lee and V. L. Kashyap. (2014) "Automatic Estimation of Flux Distributions of Astrophysical Source Populations". The Annals of Applied Statistics, 8(3), 1690-1712.
    [abstract] [journal] [arXiv] [PDF] [supplement]
  • R. K. W. Wong, F. Yao and T. C. M. Lee. (2014) "Robust Estimation for Generalized Additive Models". Journal of Computational and Graphical Statistics, 23(1), 270-289.
    ASA Section on Nonparametric Statistics Student Paper Award
    [abstract] [journal] [code]

2010

  • R. C. S. Lai, T. C. M. Lee, R. K. W. Wong and F. Yao. (2010) "Nonparametric Cepstrum Estimation via Optimal Risk Smoothing". IEEE Transactions on Signal Processing, 58(3), 1507-1514.
    [abstract] [journal]
  • R. K. W. Wong, R. C. S. Lai and T. C. M. Lee. (2010) "Structural Break Estimation of Noisy Sinusoidal Signals". Signal Processing, 90(1), 303-312.
    [abstract] [journal]