15 citations · 31 across the 18 of their papers we have counts for
7 papers · 1 filter
Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network
Tianyang Hu, Wenjia Wang, Cong Lin +1
Overparametrized neural networks trained by gradient descent (GD) can provably overfit any training data. However, the generalization guarantee may not hold for noisy data. From a…
High-Dimensional Non-Parametric Density Estimation in Mixed Smooth Sobolev Spaces
Liang Ding, Lu Zou, Wenjia Wang +2
Density estimation plays a key role in many tasks in machine learning, statistical inference, and visualization. The main bottleneck in high-dimensional density estimation is the p…
Reduced Rank Multivariate Kernel Ridge Regression
Wenjia Wang, Yi-Hui Zhou
In the multivariate regression, also referred to as multi-task learning in machine learning, the goal is to recover a vector-valued function based on noisy observations. The vector…
Eigenvector-based sparse canonical correlation analysis: Fast computation for estimation of multiple canonical vectors
Wenjia Wang, Yi-Hui Zhou
Classical canonical correlation analysis (CCA) requires matrices to be low dimensional, i.e. the number of features cannot exceed the sample size. Recent developments in CCA have m…
Uncertainty Quantification for Bayesian Optimization
Rui Tuo, Wenjia Wang
Bayesian optimization is a class of global optimization techniques. In Bayesian optimization, the underlying objective function is modeled as a realization of a Gaussian process. A…
Gaussian Processes with Input Location Error and Applications to the Composite Parts Assembly Process
Wenjia Wang, Xiaowei Yue, Benjamin Haaland +1
In this paper, we investigate Gaussian process modeling with input location error, where the inputs are corrupted by noise. Here, the best linear unbiased predictor for two cases i…
On the Inference of Applying Gaussian Process Modeling to a Deterministic Function
Wenjia Wang
Gaussian process modeling is a standard tool for building emulators for computer experiments, which are usually used to study deterministic functions, for example, a solution to a…