Raymond K. W. Wong

Orcid: 0000-0001-9342-3755

According to our database1, Raymond K. W. Wong authored at least 25 papers between 2010 and 2024.

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Bibliography

2024
Distributional Off-policy Evaluation with Bellman Residual Minimization.
CoRR, 2024

2023
Bayesian Nonlinear Tensor Regression with Functional Fused Elastic Net Prior.
Technometrics, October, 2023

Directed Cyclic Graph for Causal Discovery from Multivariate Functional Data.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Implicit Regularization for Group Sparsity.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Extending the Use of MDL for High-Dimensional Problems: Variable Selection, Robust Fitting, and Additive Modeling.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Benefits of Jointly Training Autoencoders: An Improved Neural Tangent Kernel Analysis.
IEEE Trans. Inf. Theory, 2021

Projected State-action Balancing Weights for Offline Reinforcement Learning.
CoRR, 2021

Implicit Sparse Regularization: The Impact of Depth and Early Stopping.
CoRR, 2021

Tensor Linear Regression: Degeneracy and Solution.
IEEE Access, 2021

Matrix Completion with Model-free Weighting.
Proceedings of the 38th International Conference on Machine Learning, 2021

2020
Network Estimation via Graphon With Node Features.
IEEE Trans. Netw. Sci. Eng., 2020

CP Degeneracy in Tensor Regression.
CoRR, 2020

Median Matrix Completion: from Embarrassment to Optimality.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Locally linear embedding with additive noise.
Pattern Recognit. Lett., 2019

Provably Accurate Double-Sparse Coding.
J. Mach. Learn. Res., 2019

Nonparametric operator-regularized covariance function estimation for functional data.
Comput. Stat. Data Anal., 2019

On the Dynamics of Gradient Descent for Autoencoders.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Matrix Completion under Low-Rank Missing Mechanism.
CoRR, 2018

Autoencoders Learn Generative Linear Models.
CoRR, 2018

A Provable Approach for Double-Sparse Coding.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Matrix Completion with Noisy Entries and Outliers.
J. Mach. Learn. Res., 2017

The impact of discharge inversion effect on learning SRAM power-up statistics.
Proceedings of the 2017 Asian Hardware Oriented Security and Trust Symposium, 2017

2014
Autocorrelation in Short Time Series with Trends: a Simulation Study of estimation and significance Testing with Application to Air Quality Data.
Adv. Data Sci. Adapt. Anal., 2014

2010
Nonparametric cepstrum estimation via optimal risk smoothing.
IEEE Trans. Signal Process., 2010

Structural break estimation of noisy sinusoidal signals.
Signal Process., 2010


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