no code implementations • 4 Mar 2024 • Wenjing Zhang, Wei zhang
Instead of making behavioral decisions directly from the exponentially expanding joint observational-action space, subtask-based multi-agent reinforcement learning (MARL) methods enable agents to learn how to tackle different subtasks.
Hierarchical Reinforcement Learning Multi-agent Reinforcement Learning +4
no code implementations • 21 Feb 2024 • Jianqiang Shen, Yuchin Juan, Shaobo Zhang, Ping Liu, Wen Pu, Sriram Vasudevan, Qingquan Song, Fedor Borisyuk, Kay Qianqi Shen, Haichao Wei, Yunxiang Ren, Yeou S. Chiou, Sicong Kuang, Yuan Yin, Ben Zheng, Muchen Wu, Shaghayegh Gharghabi, Xiaoqing Wang, Huichao Xue, Qi Guo, Daniel Hewlett, Luke Simon, Liangjie Hong, Wenjing Zhang
Web-scale search systems typically tackle the scalability challenge with a two-step paradigm: retrieval and ranking.
no code implementations • 20 Feb 2024 • Ping Liu, Haichao Wei, Xiaochen Hou, Jianqiang Shen, Shihai He, Kay Qianqi Shen, Zhujun Chen, Fedor Borisyuk, Daniel Hewlett, Liang Wu, Srikant Veeraraghavan, Alex Tsun, Chengming Jiang, Wenjing Zhang
This methodology decouples the training of the GNN model from that of existing Deep Neural Nets (DNN) models, eliminating the need for frequent GNN retraining while maintaining up-to-date graph signals in near realtime, allowing for the effective integration of GNN insights through transfer learning.
no code implementations • 1 Jan 2023 • Wenjing Zhang, Yining Wang, Mingzhe Chen, Tao Luo, Dusit Niyato
In this paper, a semantic communication framework for image transmission is developed.
Multi-agent Reinforcement Learning Reinforcement Learning (RL)
no code implementations • 6 Aug 2022 • Haoyuan Zhang, Yonghong Hou, Wenjing Zhang, Wanqing Li
The CPM identifies non-self positives in a contextual queue to boost learning.