42 citations · 97 across the 12 of their papers we have counts for
19 papers
Identifiable Generative Models for Missing Not at Random Data Imputation
Chao Ma, Cheng Zhang
Real-world datasets often have missing values associated with complex generative processes, where the cause of the missingness may not be fully observed. This is known as missing n…
A Riemannian Mean Field Formulation for Two-layer Neural Networks with Batch Normalization
Chao Ma, Lexing Ying
The training dynamics of two-layer neural networks with batch normalization (BN) is studied. It is written as the training dynamics of a neural network without BN on a Riemannian m…
Achieving Adversarial Robustness Requires An Active Teacher
Chao Ma, Lexing Ying
A new understanding of adversarial examples and adversarial robustness is proposed by decoupling the data generator and the label generator (which we call the teacher). In our fram…
Complexity Measures for Neural Networks with General Activation Functions Using Path-based Norms
Zhong Li, Chao Ma, Lei Wu
A simple approach is proposed to obtain complexity controls for neural networks with general activation functions. The approach is motivated by approximating the general activation…
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't
Weinan E, Chao Ma, Stephan Wojtowytsch +1
The purpose of this article is to review the achievements made in the last few years towards the understanding of the reasons behind the success and subtleties of neural network-ba…
The Slow Deterioration of the Generalization Error of the Random Feature Model
Chao Ma, Lei Wu, Weinan E
The random feature model exhibits a kind of resonance behavior when the number of parameters is close to the training sample size. This behavior is characterized by the appearance…