A New Theoretical Perspective on Data Heterogeneity in Federated Optimization
- Jiayi Wang
- Shiqiang Wang
- et al.
- 2023
- ICML 2023
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Towards a Theoretical and Practical Understanding of One-Shot Federated Learning with Fisher Information
- Divyansh Jhunjhunwala
- Shiqiang Wang
- et al.
- 2023
- ICML 2023
International Workshop on Federated Learning in the Age of Foundation Models
- Jinghui Chen
- Lixin Fan
- et al.
- 2023
- NeurIPS 2023
Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities
- Zheng Xu
- Peter Kairouz
- et al.
- 2023
- ICML 2023
Federated Learning: Recent Advances and New Challenges
- 2022
- NeurIPS 2022
Flexible Vertical Federated Learning With Heterogeneous Parties
- Timothy Castiglia
- Shiqiang Wang
- et al.
- 2023
- IEEE TNNLS
Model Pruning Enables Efficient Federated Learning on Edge Devices
- Yuang Jiang
- Shiqiang Wang
- et al.
- 2021
- IEEE TNNLS
Preparing Good Data for Generative AI: Challenges and Approaches (Good-Data)
- David Vazquez
- Laure Berti-equille
- et al.
- 2025
- AAAI 2025
Gradient-based Uncertainty Attribution for Explainable Bayesian Deep Learning
- Hanjing Wang
- Dhiraj Joshi
- et al.
- 2023
- CVPR 2023
FLEdge: Benchmarking Federated Learning Applications in Edge Computing Systems
- Herbert Woisetschläger
- Alexander Erben
- et al.
- 2024
- Middleware 2024