1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Preventing Catastrophic Overfitting in Fast Adversarial Training: A Bi-level Optimization Perspective
Zhaoxin Wang, Handing Wang, Cong Tian +1
Adversarial training (AT) has become an effective defense method against adversarial examples (AEs) and it is typically framed as a bi-level optimization problem. Among various AT…
cs.AI2024★ 1 cited
Exploring Knowledge Transfer in Evolutionary Many-task Optimization: A Complex Network Perspective
Yudong Yang, Kai Wu, Xiangyi Teng +3
The field of evolutionary many-task optimization (EMaTO) is increasingly recognized for its ability to streamline the resolution of optimization challenges with repetitive characte…
cs.NE2024
Interpreting Multi-objective Evolutionary Algorithms via Sokoban Level Generation
Qingquan Zhang, Yuchen Li, Yuhang Lin +2
This paper presents an interactive platform to interpret multi-objective evolutionary algorithms. Sokoban level generation is selected as a showcase for its widespread use in proce…