306 citations
- The University of SydneyAU9 papers
- University of Science and Technology of ChinaCN7 papers
- Chinese Academy of SciencesCN6 papers
- JDSU (United States)US6 papers
- University of Chinese Academy of SciencesCN5 papers
- Beihang UniversityCN4 papers
- Tsinghua UniversityCN4 papers
- Association for Computing MachineryUS3 papers
- Baidu (China)CN3 papers
- City University of Hong KongHK3 papers
- Institute of Computing TechnologyCN3 papers
- National University of SingaporeSG3 papers
10 papers · 1 filter
Personalized Federated Continual Learning via Multi-granularity Prompt
Hao Yu, Xin Yang, Xin Gao +4
Personalized Federated Continual Learning (PFCL) is a new practical scenario that poses greater challenges in sharing and personalizing knowledge. PFCL not only relies on knowledge…
Federated Continual Learning via Knowledge Fusion: A Survey
Xin Yang, Hao Yu, Xin Gao +3
Data privacy and silos are nontrivial and greatly challenging in many real-world applications. Federated learning is a decentralized approach to training models across multiple loc…
Graph Neural Processes for Spatio-Temporal Extrapolation
Junfeng Hu, Yuxuan Liang, Zhencheng Fan +3
We study the task of spatio-temporal extrapolation that generates data at target locations from surrounding contexts in a graph. This task is crucial as sensors that collect data a…
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
Qingsong Zhang, Bin Gu, Cheng Deng +4
Vertical federated learning (VFL) is an effective paradigm of training the emerging cross-organizational (e.g., different corporations, companies and organizations) collaborative l…
Category-Specific CNN for Visual-aware CTR Prediction at JD.com
Hu Liu, Jing Lu, Hao Yang +8
As one of the largest B2C e-commerce platforms in China, JD com also powers a leading advertising system, serving millions of advertisers with fingertip connection to hundreds of m…
CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data
Xiang Li, Ben Kao, Caihua Shan +2
We study the problem of applying spectral clustering to cluster multi-scale data, which is data whose clusters are of various sizes and densities. Traditional spectral clustering t…