activity
20182020
most citedModeling the Biological Pathology Continuum with HSIC-regularized Wasserstein Auto-encoders

2 citations · 2 across the 1 of their papers we have counts for

collaborators

7 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…

stat.ML2019

Stochastic Runge-Kutta Accelerates Langevin Monte Carlo and Beyond

Xuechen Li, Denny Wu, Lester Mackey +1

Sampling with Markov chain Monte Carlo methods often amounts to discretizing some continuous-time dynamics with numerical integration. In this paper, we establish the convergence r…

cs.LG20192 cited

Modeling the Biological Pathology Continuum with HSIC-regularized Wasserstein Auto-encoders

Denny Wu, Hirofumi Kobayashi, Charles Ding +2

A crucial challenge in image-based modeling of biomedical data is to identify trends and features that separate normality and pathology. In many cases, the morphology of the imaged…

stat.ML2018

Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator

Makoto Yamada, Denny Wu, Yao-Hung Hubert Tsai +3

Measuring divergence between two distributions is essential in machine learning and statistics and has various applications including binary classification, change point detection,…

cs.IT2018

"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study

Denny Wu, Yixiu Zhao, Yao-Hung Hubert Tsai +2

Recent works investigated the generalization properties in deep neural networks (DNNs) by studying the Information Bottleneck in DNNs. However, the mea- surement of the mutual info…