3 papers
cs.AI2023
Cooperation or Competition: Avoiding Player Domination for Multi-Target Robustness via Adaptive Budgets
Yimu Wang, Dinghuai Zhang, Yihan Wu +2
Despite incredible advances, deep learning has been shown to be susceptible to adversarial attacks. Numerous approaches have been proposed to train robust networks both empirically…
cs.SI2023
Optimal Intervention on Weighted Networks via Edge Centrality
Dongyue Li, Tina Eliassi-Rad, Hongyang R. Zhang
Suppose there is a spreading process such as an infectious disease propagating on a graph. How would we reduce the number of affected nodes in the spreading process? This question…
cs.LG2022
Nash Equilibria and Pitfalls of Adversarial Training in Adversarial Robustness Games
Maria-Florina Balcan, Rattana Pukdee, Pradeep Ravikumar +1
Adversarial training is a standard technique for training adversarially robust models. In this paper, we study adversarial training as an alternating best-response strategy in a 2-…