35 citations · 174 across the 20 of their papers we have counts for
5 papers · 1 filter
Who, What, Why and How? Towards the Monetary Incentive in Crowd Collaboration: A Case Study of Github's Sponsor Mechanism
Xunhui Zhang, Tao Wang, Yue Yu +3
While many forms of financial support are currently available, there are still many complaints about inadequate financing from software maintainers. In May 2019, GitHub, the world'…
Pull Request Latency Explained: An Empirical Overview
Xunhui Zhang, Yue Yu, Tao Wang +2
Pull request latency evaluation is an essential application of effort evaluation in the pull-based development scenario. It can help the reviewers sort the pull request queue, remi…
KnowSR: Knowledge Sharing among Homogeneous Agents in Multi-agent Reinforcement Learning
Zijian Gao, Kele Xu, Bo Ding +3
Recently, deep reinforcement learning (RL) algorithms have made great progress in multi-agent domain. However, due to characteristics of RL, training for complex tasks would be res…
KnowRU: Knowledge Reusing via Knowledge Distillation in Multi-agent Reinforcement Learning
Zijian Gao, Kele Xu, Bo Ding +3
Recently, deep Reinforcement Learning (RL) algorithms have achieved dramatically progress in the multi-agent area. However, training the increasingly complex tasks would be time-co…
FedH2L: Federated Learning with Model and Statistical Heterogeneity
Yiying Li, Wei Zhou, Huaimin Wang +2
Federated learning (FL) enables distributed participants to collectively learn a strong global model without sacrificing their individual data privacy. Mainstream FL approaches req…