2 citations · 2 across the 1 of their papers we have counts for
4 papers
Towards Theoretical Understanding of Large Batch Training in Stochastic Gradient Descent
Xiaowu Dai, Yuhua Zhu
Stochastic gradient descent (SGD) is almost ubiquitously used for training non-convex optimization tasks. Recently, a hypothesis proposed by Keskar et al. [2017] that large batch m…
Selection and Estimation Optimality in High Dimensions with the TWIN Penalty
Xiaowu Dai, Jared D. Huling
We introduce a novel class of variable selection penalties called TWIN, which provides sensible data-adaptive penalization. Under a linear sparsity regime and random Gaussian desig…
Another Look at Statistical Calibration: A Non-Asymptotic Theory and Prediction-Oriented Optimality
Xiaowu Dai, Peter Chien
We provide another look at the statistical calibration problem in computer models. This viewpoint is inspired by two overarching practical considerations of computer models: (i) ma…
Minimax Optimal Rates of Estimation in Functional ANOVA Models with Derivatives
Xiaowu Dai, Peter Chien
We establish minimax optimal rates of convergence for nonparametric estimation in functional ANOVA models when data from first-order partial derivatives are available. Our results…