36 citations · 80 across the 8 of their papers we have counts for
8 papers
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo +5
It is challenging for reinforcement learning (RL) algorithms to succeed in real-world applications like financial trading and logistic system due to the noisy observation and envir…
Curriculum Offline Imitation Learning
Minghuan Liu, Hanye Zhao, Zhengyu Yang +4
Offline reinforcement learning (RL) tasks require the agent to learn from a pre-collected dataset with no further interactions with the environment. Despite the potential to surpas…
SSFL: Tackling Label Deficiency in Federated Learning via Personalized Self-Supervision
Chaoyang He, Zhengyu Yang, Erum Mushtaq +3
Federated Learning (FL) is transforming the ML training ecosystem from a centralized over-the-cloud setting to distributed training over edge devices in order to strengthen data pr…
SimPLE: Similar Pseudo Label Exploitation for Semi-Supervised Classification
Zijian Hu, Zhengyu Yang, Xuefeng Hu +1
A common classification task situation is where one has a large amount of data available for training, but only a small portion is annotated with class labels. The goal of semi-sup…
To Follow or not to Follow: Selective Imitation Learning from Observations
Youngwoon Lee, Edward S. Hu, Zhengyu Yang +1
Learning from demonstrations is a useful way to transfer a skill from one agent to another. While most imitation learning methods aim to mimic an expert skill by following the demo…
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
Youngwoon Lee, Edward S. Hu, Zhengyu Yang +2
The IKEA Furniture Assembly Environment is one of the first benchmarks for testing and accelerating the automation of complex manipulation tasks. The environment is designed to adv…
Deep Landscape Forecasting for Real-time Bidding Advertising
Kan Ren, Jiarui Qin, Lei Zheng +3
The emergence of real-time auction in online advertising has drawn huge attention of modeling the market competition, i.e., bid landscape forecasting. The problem is formulated as…
Deep Recurrent Survival Analysis
Kan Ren, Jiarui Qin, Lei Zheng +4
Survival analysis is a hotspot in statistical research for modeling time-to-event information with data censorship handling, which has been widely used in many applications such as…