activity
20172025
most citedUnderstanding Deep Learning Generalization by Maximum Entropy

5 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2025

Unifying Perplexing Behaviors in Modified BP Attributions through Alignment Perspective

Guanhua Zheng, Jitao Sang, Changsheng Xu

Attributions aim to identify input pixels that are relevant to the decision-making process. A popular approach involves using modified backpropagation (BP) rules to reverse decisio…

cs.LG2020

MMCGAN: Generative Adversarial Network with Explicit Manifold Prior

Guanhua Zheng, Jitao Sang, Changsheng Xu

Generative Adversarial Network(GAN) provides a good generative framework to produce realistic samples, but suffers from two recognized issues as mode collapse and unstable training…

cs.CV2020

Adaptive Adversarial Logits Pairing

Shangxi Wu, Jitao Sang, Kaiyuan Xu +2

Adversarial examples provide an opportunity as well as impose a challenge for understanding image classification systems. Based on the analysis of the adversarial training solution…

cs.LG2019

A Generalization Theory based on Independent and Task-Identically Distributed Assumption

Guanhua Zheng, Jitao Sang, Houqiang Li +2

Existing generalization theories analyze the generalization performance mainly based on the model complexity and training process. The ignorance of the task properties, which resul…

cs.LG2017★ 5 cited

Understanding Deep Learning Generalization by Maximum Entropy

Guanhua Zheng, Jitao Sang, Changsheng Xu

Deep learning achieves remarkable generalization capability with overwhelming number of model parameters. Theoretical understanding of deep learning generalization receives recent…