1 code implementation • 27 Mar 2023 • Minting Pan, Xiangming Zhu, Yitao Zheng, Yunbo Wang, Xiaokang Yang
On top of our previous work, we further consider the sparse dependencies between controllable and noncontrollable states, address the training collapse problem of state decoupling, and validate our approach in transfer learning setups.
2 code implementations • 12 Mar 2023 • Wendong Zhang, Geng Chen, Xiangming Zhu, Siyu Gao, Yunbo Wang, Xiaokang Yang
In this paper, we present a new continual learning approach for visual dynamics modeling and explore its efficacy in visual control and forecasting.
no code implementations • 24 Dec 2022 • Xiaoyu Chen, Xiangming Zhu, Yufeng Zheng, Pushi Zhang, Li Zhao, Wenxue Cheng, Peng Cheng, Yongqiang Xiong, Tao Qin, Jianyu Chen, Tie-Yan Liu
One of the key challenges in deploying RL to real-world applications is to adapt to variations of unknown environment contexts, such as changing terrains in robotic tasks and fluctuated bandwidth in congestion control.
no code implementations • 24 Jul 2022 • Quanshi Zhang, Xin Wang, Jie Ren, Xu Cheng, Shuyun Lin, Yisen Wang, Xiangming Zhu
This paper summarizes the common mechanism shared by twelve previous transferability-boosting methods in a unified view, i. e., these methods all reduce game-theoretic interactions between regional adversarial perturbations.
2 code implementations • 27 May 2022 • Minting Pan, Xiangming Zhu, Yunbo Wang, Xiaokang Yang
First, by optimizing the inverse dynamics, we encourage the world model to learn controllable and noncontrollable sources of spatiotemporal changes on isolated state transition branches.
no code implementations • ICLR 2021 • Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
We discover and prove the negative correlation between the adversarial transferability and the interaction inside adversarial perturbations.
1 code implementation • 8 Oct 2020 • Xin Wang, Jie Ren, Shuyun Lin, Xiangming Zhu, Yisen Wang, Quanshi Zhang
We discover and prove the negative correlation between the adversarial transferability and the interaction inside adversarial perturbations.