activity
20192022
most citedA Game-Theoretic Taxonomy of Visual Concepts in DNNs

7 citations · 16 across the 6 of their papers we have counts for

collaborators

11 papers

cs.LG20222 cited

Why Adversarial Training of ReLU Networks Is Difficult?

Xu Cheng, Hao Zhang, Yue Xin +3

This paper mathematically derives an analytic solution of the adversarial perturbation on a ReLU network, and theoretically explains the difficulty of adversarial training. Specifi…

cs.LG2021

A Unified Game-Theoretic Interpretation of Adversarial Robustness

Jie Ren, Die Zhang, Yisen Wang +8

This paper provides a unified view to explain different adversarial attacks and defense methods, \emph{i.e.} the view of multi-order interactions between input variables of DNNs. B…

cs.LG20214 cited

A Hypothesis for the Aesthetic Appreciation in Neural Networks

Xu Cheng, Xin Wang, Haotian Xue +2

This paper proposes a hypothesis for the aesthetic appreciation that aesthetic images make a neural network strengthen salient concepts and discard inessential concepts. In order t…

cs.LG20217 cited

A Game-Theoretic Taxonomy of Visual Concepts in DNNs

Xu Cheng, Chuntung Chu, Yi Zheng +2

In this paper, we rethink how a DNN encodes visual concepts of different complexities from a new perspective, i.e. the game-theoretic multi-order interactions between pixels in an…

cs.LG2021

A Unified Game-Theoretic Interpretation of Adversarial Robustness

Jie Ren, Die Zhang, Yisen Wang +8

This paper provides a unified view to explain different adversarial attacks and defense methods, i.e. the view of multi-order interactions between input variables of DNNs. Based on…

cs.LG2020

Technical Note: Game-Theoretic Interactions of Different Orders

Hao Zhang, Xu Cheng, Yiting Chen +1

In this study, we define interaction components of different orders between two input variables based on game theory. We further prove that interaction components of different orde…