6 citations · 7 across the 3 of their papers we have counts for
4 papers
Vertical Federated Linear Contextual Bandits
Zeyu Cao, Zhipeng Liang, Shu Zhang +5
In this paper, we investigate a novel problem of building contextual bandits in the vertical federated setting, i.e., contextual information is vertically distributed over differen…
DRFLM: Distributionally Robust Federated Learning with Inter-client Noise via Local Mixup
Bingzhe Wu, Zhipeng Liang, Yuxuan Han +3
Recently, federated learning has emerged as a promising approach for training a global model using data from multiple organizations without leaking their raw data. Nevertheless, di…
Generalized Linear Bandits with Local Differential Privacy
Yuxuan Han, Zhipeng Liang, Yang Wang +1
Contextual bandit algorithms are useful in personalized online decision-making. However, many applications such as personalized medicine and online advertising require the utilizat…
Adversarial Deep Reinforcement Learning in Portfolio Management
Zhipeng Liang, Hao Chen, Junhao Zhu +2
In this paper, we implement three state-of-art continuous reinforcement learning algorithms, Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO) and Polic…