7 citations · 9 across the 5 of their papers we have counts for
5 papers
Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift
Yijun Dong, Yuege Xie, Rachel Ward
Concept shift is a prevailing problem in natural tasks like medical image segmentation where samples usually come from different subpopulations with variant correlations between fe…
SHRIMP: Sparser Random Feature Models via Iterative Magnitude Pruning
Yuege Xie, Bobby Shi, Hayden Schaeffer +1
Sparse shrunk additive models and sparse random feature models have been developed separately as methods to learn low-order functions, where there are few interactions between vari…
AdaLoss: A computationally-efficient and provably convergent adaptive gradient method
Xiaoxia Wu, Yuege Xie, Simon Du +1
We propose a computationally-friendly adaptive learning rate schedule, "AdaLoss", which directly uses the information of the loss function to adjust the stepsize in gradient descen…
Overparameterization and generalization error: weighted trigonometric interpolation
Yuege Xie, Hung-Hsu Chou, Holger Rauhut +1
Motivated by surprisingly good generalization properties of learned deep neural networks in overparameterized scenarios and by the related double descent phenomenon, this paper ana…
Linear Convergence of Adaptive Stochastic Gradient Descent
Yuege Xie, Xiaoxia Wu, Rachel Ward
We prove that the norm version of the adaptive stochastic gradient method (AdaGrad-Norm) achieves a linear convergence rate for a subset of either strongly convex functions or non-…