activity
20182020
collaborators

9 papers

stat.ML2020

When Does Preconditioning Help or Hurt Generalization?

Shun-ichi Amari, Jimmy Ba, Roger Grosse +5

While second order optimizers such as natural gradient descent (NGD) often speed up optimization, their effect on generalization has been called into question. This work presents a…

stat.ML2020

On the Optimal Weighted Regularization in Overparameterized Linear Regression

Denny Wu, Ji Xu

We consider the linear model with in the overparameterized regime . We estimate $\ma…

math.ST2019

On the number of variables to use in principal component regression

Ji Xu, Daniel Hsu

We study least squares linear regression over uncorrelated Gaussian features that are selected in order of decreasing variance. When the number of selected features is at m…

cs.LG2019

Two models of double descent for weak features

Mikhail Belkin, Daniel Hsu, Ji Xu

The "double descent" risk curve was proposed to qualitatively describe the out-of-sample prediction accuracy of variably-parameterized machine learning models. This article provide…

cs.IT2019

Spectral Method for Phase Retrieval: an Expectation Propagation Perspective

Junjie Ma, Rishabh Dudeja, Ji Xu +2

Phase retrieval refers to the problem of recovering a signal from its phaseless measurements

math.ST2019

Consistent Risk Estimation in Moderately High-Dimensional Linear Regression

Ji Xu, Arian Maleki, Kamiar Rahnama Rad +1

Risk estimation is at the core of many learning systems. The importance of this problem has motivated researchers to propose different schemes, such as cross validation, generalize…