no code implementations • COLING 2022 • Zhitong Yang, Bo wang, Jinfeng Zhou, Yue Tan, Dongming Zhao, Kun Huang, Ruifang He, Yuexian Hou
We design a global reinforcement learning with the planned paths to flexibly adjust the local response generation model towards the global target.
1 code implementation • 9 Feb 2024 • Yue Tan, Olaf Wysocki, Ludwig Hoegner, Uwe Stilla
3D building models with facade details are playing an important role in many applications now.
1 code implementation • 23 Nov 2022 • Yue Tan, Yixin Liu, Guodong Long, Jing Jiang, Qinghua Lu, Chengqi Zhang
Inspired by this, we propose FedStar, an FGL framework that extracts and shares the common underlying structure information for inter-graph federated learning tasks.
2 code implementations • 21 Sep 2022 • Yue Tan, Guodong Long, Jie Ma, Lu Liu, Tianyi Zhou, Jing Jiang
To prevent these issues from hindering the deployment of FL systems, we propose a lightweight framework where clients jointly learn to fuse the representations generated by multiple fixed pre-trained models rather than training a large-scale model from scratch.
no code implementations • 24 Aug 2021 • Guodong Long, Tao Shen, Yue Tan, Leah Gerrard, Allison Clarke, Jing Jiang
Implementing an open innovation framework in the healthcare industry, namely open health, is to enhance innovation and creative capability of health-related organisations by building a next-generation collaborative framework with partner organisations and the research community.
no code implementations • 24 Aug 2021 • Guodong Long, Yue Tan, Jing Jiang, Chengqi Zhang
In the near future, it is foreseeable to have decentralized data ownership in the finance sector using federated learning.
4 code implementations • 1 May 2021 • Yue Tan, Guodong Long, Lu Liu, Tianyi Zhou, Qinghua Lu, Jing Jiang, Chengqi Zhang
Heterogeneity across clients in federated learning (FL) usually hinders the optimization convergence and generalization performance when the aggregation of clients' knowledge occurs in the gradient space.
no code implementations • 12 Mar 2021 • Xiaoyun Chen, Yue Tan, Yuan Chen
For $b\bar{s}q\bar{q}$ system with $J=0$, some resonance states are also found.
High Energy Physics - Phenomenology
no code implementations • 25 Feb 2021 • Shaoxiong Ji, Yue Tan, Teemu Saravirta, Zhiqin Yang, Yixin Liu, Lauri Vasankari, Shirui Pan, Guodong Long, Anwar Walid
Federated learning is a new learning paradigm that decouples data collection and model training via multi-party computation and model aggregation.
no code implementations • 5 Jun 2020 • Yue Tan, Chunjing Hu, Kuan Zhang, Kan Zheng, Ethan A. Davis, Jae Sung Park
Anomaly detection for non-linear dynamical system plays an important role in ensuring the system stability.
no code implementations • 7 Feb 2020 • Lei Lei, Yue Tan, Glenn Dahlenburg, Wei Xiang, Kan Zheng
Microgrids (MGs) are small, local power grids that can operate independently from the larger utility grid.
no code implementations • 22 Jul 2019 • Lei Lei, Yue Tan, Kan Zheng, Shiwen Liu, Kuan Zhang, Xuemin, Shen
Next, a comprehensive survey of the state-of-art research on DRL for AIoT is presented, where the existing works are classified and summarized under the umbrella of the proposed general DRL model.
no code implementations • 12 Feb 2019 • Yue Tan, Kan Zheng, Lei Lei
In order to maximize detection precision rate as well as the recall rate, this paper proposes an in-vehicle multi-source fusion scheme in Keyword Spotting (KWS) System for vehicle applications.