11 citations · 30 across the 19 of their papers we have counts for
4 papers · 1 filter
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…
High-Dimensional Smoothing Splines and Application in Alzheimer's Disease Prediction Using Magnetic Resonance Imaging
Xiaowu Dai
Recent evidence has shown that structural magnetic resonance imaging (MRI) is an effective tool for Alzheimer's disease (AD) prediction and diagnosis. While traditional MRI-based d…
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…