no code implementations • 7 Mar 2024 • Md Sirajul Islam, Simin Javaherian, Fei Xu, Xu Yuan, Li Chen, Nian-Feng Tzeng
Clustered federated learning (CFL) addresses this challenge by grouping clients based on the similarity of their data distributions.
1 code implementation • IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2023 • Xu Yuan, Zheng Zhang, Xunguang Wang, Lin Wu
Further, we, for the first time, formulate the formalized adversarial training of deep hashing into a unified minimax optimization under the guidance of the generated mainstay codes.
1 code implementation • ICCV 2023 • Fudong Lin, Summer Crawford, Kaleb Guillot, Yihe Zhang, Yan Chen, Xu Yuan, Li Chen, Shelby Williams, Robert Minvielle, Xiangming Xiao, Drew Gholson, Nicolas Ashwell, Tri Setiyono, Brenda Tubana, Lu Peng, Magdy Bayoumi, Nian-Feng Tzeng
In this work, we develop a deep learning-based solution, namely Multi-Modal Spatial-Temporal Vision Transformer (MMST-ViT), for predicting crop yields at the county level across the United States, by considering the effects of short-term meteorological variations during the growing season and the long-term climate change on crops.
no code implementations • 8 Aug 2023 • Haomin Zhuang, Mingxian Yu, Hao Wang, Yang Hua, Jian Li, Xu Yuan
Federated learning (FL) has been widely deployed to enable machine learning training on sensitive data across distributed devices.
no code implementations • ICCV 2023 • Rui Chen, Qiyu Wan, Pavana Prakash, Lan Zhang, Xu Yuan, Yanmin Gong, Xin Fu, Miao Pan
However, practical deployment of FL over mobile devices is very challenging because (i) conventional FL incurs huge training latency for mobile devices due to interleaved local computing and communications of model updates, (ii) there are heterogeneous training data across mobile devices, and (iii) mobile devices have hardware heterogeneity in terms of computing and communication capabilities.
no code implementations • 19 Oct 2022 • Xu Yuan, Chen Xu, Qiwei Chen, Tao Zhuang, Hongjie Chen, Chao Li, Junfeng Ge
This paper proposes a Hierarchical Multi-Interest Co-Network (HCN) to capture users' diverse interests in the coarse-grained ranking stage.
no code implementations • 28 Aug 2021 • Hanfei Yu, Hao Wang, Jian Li, Xu Yuan, Seung-Jong Park
Serverless computing automates fine-grained resource scaling and simplifies the development and deployment of online services with stateless functions.
no code implementations • 26 Jun 2021 • Xu Yuan, Hongshen Chen, Yonghao Song, Xiaofang Zhao, Zhuoye Ding, Zhen He, Bo Long
In this paper, we propose a model, SSI, to improve sequential recommendation consistency with Self-Supervised Imitation.
no code implementations • IEEE 2021 • Fangming Zhong∗, Guangze Wang, Zhikui Chen, Xu Yuan, Feng Xia
Generalized zero-shot learning (GZSL) has attracted consid- erable attention recently, which trains models with data from seen classes and tests on data from both seen and unseen classes.
no code implementations • 22 Feb 2021 • Raphaël Côte, Xu Yuan
We consider the nonlinear damped Klein-Gordon equation \[ \partial_{tt}u+2\alpha\partial_{t}u-\Delta u+u-|u|^{p-1}u=0 \quad \text{on} \ \ [0,\infty)\times \mathbb{R}^N \] with $\alpha>0$, $2 \le N\le 5$ and energy subcritical exponents $p>2$.
Analysis of PDEs