no code implementations • 1 Mar 2023 • Haizhou Du, Chengdong Ni
Emerging distributed applications recently boosted the development of decentralized machine learning, especially in IoT and edge computing fields.
no code implementations • 28 Oct 2022 • Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker
Distributed machine learning (DML) can be an important capability for modern military to take advantage of data and devices distributed at multiple vantage points to adapt and learn.
no code implementations • 29 Jan 2022 • Haizhou Du, Ryan Yang, Yijian Chen, Qiao Xiang, Andre Wibisono, Wei Huang
In this paper, we analyze properties of the WPM and rigorously prove convergence properties of our aggregation mechanism.
no code implementations • 21 Nov 2021 • Haizhou Du, Zong Yan, Qiao Xiang, Qinqing Zhan
The core of Vulcan is a novel, compact graph embedding that transforms highdimensional graph structure data (i. e., path-changed information) into a low-dimensional vector representation.
no code implementations • 21 Nov 2021 • Yukun Cao, Yijia Tang, Ziyue Wei, ChengKun Jin, Zeyu Miao, Yixin Fang, Haizhou Du, Feifei Xu
To solve those issues, we present a sentiment analysis model named Isomer, which performs a dual-channel attention on heterogeneous dependency graphs incorporating external knowledge, to effectively integrate other additional information.
no code implementations • 18 Sep 2021 • Haizhou Du, Xiaojie Feng, Qiao Xiang, Haoyu Liu
Specifically, in LGC, local gradients from a device is coded into several layers and each layer is sent to the FL server along a different channel.
1 code implementation • 11 Oct 2020 • Feifei Xu, Xinpeng Wang, Yunpu Ma, Volker Tresp, Yuyi Wang, Shanlin Zhou, Haizhou Du
In our work, we aim to design an emotional line for each character that considers multiple emotions common in psychological theories, with the goal of generating stories with richer emotional changes in the characters.