# Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification

@article{Xu2021TraversingTL, title={Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification}, author={Shaojie Xu and Joel Vaughan and Jie Chen and Aijun Zhang and A. Sudjianto}, journal={ArXiv}, year={2021}, volume={abs/2111.08922} }

Although neural networks (NNs) with ReLU activation functions have found success in a wide range of applications, their adoption in risk-sensitive settings has been limited by the concerns on robustness and interpretability. Previous works to examine robustness and to improve interpretability partially exploited the piecewise linear function form of ReLU NNs. In this paper, we explore the unique topological structure that ReLU NNs create in the input space, identifying the adjacency among the…

## One Citation

Support Vectors and Gradient Dynamics for Implicit Bias in ReLU Networks

- Computer Science
- 2022

This work examines the gradient flow dynamics in the parameter space when training single-neuron ReLU networks, and discovers implicit bias in terms of support vectors in ReLU Networks, which play a key role in why and how Re LU networks generalize well.

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