2 citations · 3 across the 3 of their papers we have counts for
4 papers
Phasic Diversity Optimization for Population-Based Reinforcement Learning
Jingcheng Jiang, Haiyin Piao, Yu Fu +4
Reviewing the previous work of diversity Rein-forcement Learning,diversity is often obtained via an augmented loss function,which requires a balance between reward and diversity.Ge…
Multiform Evolution for High-Dimensional Problems with Low Effective Dimensionality
Yaqing Hou, Mingyang Sun, Abhishek Gupta +4
In this paper, we scale evolutionary algorithms to high-dimensional optimization problems that deceptively possess a low effective dimensionality (certain dimensions do not signifi…
OVD-Explorer: Optimism Should Not Be the Sole Pursuit of Exploration in Noisy Environments
Jinyi Liu, Zhi Wang, Yan Zheng +6
In reinforcement learning, the optimism in the face of uncertainty (OFU) is a mainstream principle for directing exploration towards less explored areas, characterized by higher un…
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks
Yang Wang, Bo Dong, Ke Xu +4
Deep Neural Networks (DNNs) are widely used for computer vision tasks. However, it has been shown that deep models are vulnerable to adversarial attacks, i.e., their performances d…