no code implementations • 6 Feb 2023 • Jiajun Wu, Steve Drew, Fan Dong, Zhuangdi Zhu, Jiayu Zhou
The ultra-low latency requirements of 5G/6G applications and privacy constraints call for distributed machine learning systems to be deployed at the edge.
no code implementations • 29 Sep 2021 • Boyang Liu, Zhuangdi Zhu, Pang-Ning Tan, Jiayu Zhou
We first discuss the limitations of directly using the noisy-label defense algorithms to defend against backdoor attacks.
1 code implementation • the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining 2021 • Junyuan Hong, Zhuangdi Zhu, Shuyang Yu, Zhangyang Wang, Hiroko Dodge, Jiayu Zhou
While adversarial learning is commonly used in centralized learning for mitigating bias, there are significant barriers when extending it to the federated framework.
4 code implementations • 20 May 2021 • Zhuangdi Zhu, Junyuan Hong, Jiayu Zhou
Federated Learning (FL) is a decentralized machine-learning paradigm, in which a global server iteratively averages the model parameters of local users without accessing their data.
1 code implementation • NeurIPS 2020 • Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou
To further accelerate the learning procedure, we regulate the policy update with an inverse action model, which assists distribution matching from the perspective of mode-covering.
no code implementations • 16 Sep 2020 • Zhuangdi Zhu, Kaixiang Lin, Anil K. Jain, Jiayu Zhou
Reinforcement learning is a learning paradigm for solving sequential decision-making problems.
1 code implementation • 1 Apr 2020 • Zhuangdi Zhu, Kaixiang Lin, Bo Dai, Jiayu Zhou
SAIL bridges the advantages of IL and RL to reduce the sample complexity substantially, by effectively exploiting sup-optimal demonstrations and efficiently exploring the environment to surpass the demonstrated performance.