2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.HC2023
Rescue Conversations from Dead-ends: Efficient Exploration for Task-oriented Dialogue Policy Optimization
Yangyang Zhao, Zhenyu Wang, Mehdi Dastani +1
Training a dialogue policy using deep reinforcement learning requires a lot of exploration of the environment. The amount of wasted invalid exploration makes their learning ineffic…
cs.CL2020★ 2 cited
Automatic Curriculum Learning With Over-repetition Penalty for Dialogue Policy Learning
Yangyang Zhao, Zhenyu Wang, Zhenhua Huang
Dialogue policy learning based on reinforcement learning is difficult to be applied to real users to train dialogue agents from scratch because of the high cost. User simulators, w…
cs.SI2019
Network2Vec Learning Node Representation Based on Space Mapping in Networks
Huang Zhenhua, Wang Zhenyu, Zhang Rui +3
Complex networks represented as node adjacency matrices constrains the application of machine learning and parallel algorithms. To address this limitation, network embedding (i.e.,…