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- Beijing Academy of Artificial IntelligenceCN102 papers
- Shanghai Jiao Tong UniversityCN46 papers
- Chinese University of Hong KongHK26 papers
- Tsinghua UniversityCN25 papers
- Fudan UniversityCN21 papers
- Group Sense (China)CN17 papers
- Northwestern Polytechnical UniversityCN14 papers
- ShangHai JiAi Genetics & IVF InstituteCN14 papers
- University of Science and Technology of ChinaCN14 papers
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6 papers · 2 filters
Vertical Federated Learning: Concepts, Advances and Challenges
Yang Liu, Yan Kang, Tianyuan Zou +6
Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with different features about the same set of users jointly train machine learning models w…
Jointly Contrastive Representation Learning on Road Network and Trajectory
Zhenyu Mao, Ziyue Li, Dedong Li +2
Road network and trajectory representation learning are essential for traffic systems since the learned representation can be directly used in various downstream tasks (e.g., traff…
A Data Driven Method for Multi-step Prediction of Ship Roll Motion in High Sea States
Dan Zhang, Xi Zhou, Zi-Hao Wang +2
Ship roll motion in high sea states has large amplitudes and nonlinear dynamics, and its prediction is significant for operability, safety, and survivability. This paper presents a…
Stochastic Zeroth Order Gradient and Hessian Estimators: Variance Reduction and Refined Bias Bounds
Yasong Feng, Tianyu Wang
We study stochastic zeroth order gradient and Hessian estimators for real-valued functions in . We show that, via taking finite difference along random orthogonal dir…
Adaptive Discriminative Regularization for Visual Classification
Qingsong Zhao, Yi Wang, Shuguang Dou +3
How to improve discriminative feature learning is central in classification. Existing works address this problem by explicitly increasing inter-class separability and intra-class s…
Space4HGNN: A Novel, Modularized and Reproducible Platform to Evaluate Heterogeneous Graph Neural Network
Tianyu Zhao, Cheng Yang, Yibo Li +7
Heterogeneous Graph Neural Network (HGNN) has been successfully employed in various tasks, but we cannot accurately know the importance of different design dimensions of HGNNs due…