★ represents student co-author; ♦ indicates alphabetical order
Manuscripts (on open-access archives)
R. Miao★, X. Zhang and R. K. W. Wong.
(2020)
"A Wavelet-Based Independence Test for Functional Data with an Application to MEG Functional Connectivity".
AbstractarXiv
Y. Zhou★, R. K. W. Wong and K. He.
(2020)
"Broadcasted Nonparametric Tensor Regression".
AbstractarXiv
T. V. Nguyen★, R. K. W. Wong and C. Hegde.
(2019)
"Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis".
AbstractarXiv
Refereed Papers
2021
J. Wang★, R. K. W. Wong and X. Zhang.
(2021+)
"Low-Rank Covariance Function Estimation for Multidimensional Functional Data".
Journal of the American Statistical Association.
ASA Section on Nonparametric Statistics Student Paper Award (J. Wang) AbstractJournalarXiv
X. Mao★, R. K. W. Wong and S. X. Chen.
(2021+)
"Matrix Completion under Low-Rank Missing Mechanism".
Statistica Sinica.
AbstractJournalarXiv
Y. Zhou★, R. K. W. Wong and K. He.
(2021)
"Tensor Linear Regression: Degeneracy and Solution".
IEEE Access, 9, 7775-7788.
AbstractJournalarXiv
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.
AbstractJournalarXiv
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.
AbstractJournal
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.
AbstractJournalarXiv
W. Liu♦, X. Mao♦ and R. K. W. Wong♦.
(2020)
"Median Matrix Completion: from Embarrassment to Optimality".
International Conference on Machine Learning (ICML).
AbstractarXiv
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.
AbstractProceedings
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.
AbstractJournalarXiv
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 AbstractProceedingsarXiv
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.
AbstractJournalSupplement
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) AbstractJournalSupplement
J. Wang★, R. K. W. Wong and T. C. M. Lee.
(2019)
"Locally Linear Embedding with Additive Noise".
Pattern Recognition Letters 123, 47-52.
AbstractJournal
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.
AbstractJournalarXivSupplementCode
2018
R. K. W. Wong and K. C. G. Chan.
(2018)
"Kernel-based Covariate Functional Balancing for Observational Studies".
Biometrika, 105(1), 199-213.
AbstractJournalPDFSupplementCode
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 AbstractProceedingsarXiv
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.
AbstractJournalarXiv
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).
AbstractProceedings
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.
AbstractJournalarXivSupplementCode
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 AbstractJournalarXivPDFSupplement
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.
AbstractJournalarXivPDFCode
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.
AbstractJournal
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.
AbstractJournalarXivPDFSupplement
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 AbstractJournalCode
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.
AbstractJournal
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.
AbstractJournal