332 citations · 895 across the 68 of their papers we have counts for
5 papers · 1 filter
Learning Sample Reweighting for Accuracy and Adversarial Robustness
Chester Holtz, Tsui-Wei Weng, Gal Mishne
There has been great interest in enhancing the robustness of neural network classifiers to defend against adversarial perturbations through adversarial training, while balancing th…
Quantifying Safety of Learning-based Self-Driving Control Using Almost-Barrier Functions
Zhizhen Qin, Tsui-Wei Weng, Sicun Gao
Path-tracking control of self-driving vehicles can benefit from deep learning for tackling longstanding challenges such as nonlinearity and uncertainty. However, deep neural contro…
CLIP-Dissect: Automatic Description of Neuron Representations in Deep Vision Networks
Tuomas Oikarinen, Tsui-Wei Weng
In this paper, we propose CLIP-Dissect, a new technique to automatically describe the function of individual hidden neurons inside vision networks. CLIP-Dissect leverages recent ad…
Min-Max Bilevel Multi-objective Optimization with Applications in Machine Learning
Alex Gu, Songtao Lu, Parikshit Ram +1
We consider a generic min-max multi-objective bilevel optimization problem with applications in robust machine learning such as representation learning and hyperparameter optimizat…
Attacking c-MARL More Effectively: A Data Driven Approach
Nhan H. Pham, Lam M. Nguyen, Jie Chen +3
In recent years, a proliferation of methods were developed for cooperative multi-agent reinforcement learning (c-MARL). However, the robustness of c-MARL agents against adversarial…