Saved in:
| Main Authors: | Scott, Jonathan, Zakerinia, Hossein, Lampert, Christoph H. |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2306.05515 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
by: Zakerinia, Hossein, et al.
Published: (2025)
by: Zakerinia, Hossein, et al.
Published: (2025)
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
by: Zakerinia, Hossein, et al.
Published: (2025)
by: Zakerinia, Hossein, et al.
Published: (2025)
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
by: Zakerinia, Hossein, et al.
Published: (2024)
by: Zakerinia, Hossein, et al.
Published: (2024)
From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning
by: Zakerinia, Hossein, et al.
Published: (2025)
by: Zakerinia, Hossein, et al.
Published: (2025)
From Privacy to Generalization: Linear Max-Information Bounds for DP-SGD
by: Lampert, Christoph H., et al.
Published: (2026)
by: Lampert, Christoph H., et al.
Published: (2026)
Communication-Efficient Federated Learning With Data and Client Heterogeneity
by: Zakerinia, Hossein, et al.
Published: (2022)
by: Zakerinia, Hossein, et al.
Published: (2022)
DP-KAN: Differentially Private Kolmogorov-Arnold Networks
by: Kalinin, Nikita P., et al.
Published: (2024)
by: Kalinin, Nikita P., et al.
Published: (2024)
Differentially Private Federated $k$-Means Clustering with Server-Side Data
by: Scott, Jonathan, et al.
Published: (2025)
by: Scott, Jonathan, et al.
Published: (2025)
FedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated Learning
by: Tastan, Nurbek, et al.
Published: (2024)
by: Tastan, Nurbek, et al.
Published: (2024)
Learning Quantized Continuous Controllers for Integer Hardware
by: Kresse, Fabian, et al.
Published: (2025)
by: Kresse, Fabian, et al.
Published: (2025)
Differentiable Weightless Controllers: Learning Logic Circuits for Continuous Control
by: Kresse, Fabian, et al.
Published: (2025)
by: Kresse, Fabian, et al.
Published: (2025)
Scalable Interconnect Learning in Boolean Networks
by: Kresse, Fabian, et al.
Published: (2025)
by: Kresse, Fabian, et al.
Published: (2025)
Learn What You Need in Personalized Federated Learning
by: Lv, Kexin, et al.
Published: (2024)
by: Lv, Kexin, et al.
Published: (2024)
Personalized Federated Learning for Gradient Alignment
by: Kim, Dongwon, et al.
Published: (2026)
by: Kim, Dongwon, et al.
Published: (2026)
Byzantine-Robust Federated Learning with Learnable Aggregation Weights
by: Parsa, Javad, et al.
Published: (2025)
by: Parsa, Javad, et al.
Published: (2025)
Personalized Federated Learning via Learning Dynamic Graphs
by: Zhou, Ziran, et al.
Published: (2025)
by: Zhou, Ziran, et al.
Published: (2025)
Spectral Co-Distillation for Personalized Federated Learning
by: Chen, Zihan, et al.
Published: (2024)
by: Chen, Zihan, et al.
Published: (2024)
Sheaf HyperNetworks for Personalized Federated Learning
by: Nguyen, Bao, et al.
Published: (2024)
by: Nguyen, Bao, et al.
Published: (2024)
Federated Ensemble Learning with Progressive Model Personalization
by: Emrani, Ala, et al.
Published: (2026)
by: Emrani, Ala, et al.
Published: (2026)
Personalized Subgraph Federated Learning with Sheaf Collaboration
by: Liang, Wenfei, et al.
Published: (2025)
by: Liang, Wenfei, et al.
Published: (2025)
Harmonizing Generalization and Personalization in Federated Prompt Learning
by: Cui, Tianyu, et al.
Published: (2024)
by: Cui, Tianyu, et al.
Published: (2024)
Optimizing Personalized Federated Learning through Adaptive Layer-Wise Learning
by: Chen, Weihang, et al.
Published: (2024)
by: Chen, Weihang, et al.
Published: (2024)
Few-for-Many Personalized Federated Learning
by: Guo, Ping, et al.
Published: (2026)
by: Guo, Ping, et al.
Published: (2026)
Personalized Federated Learning for Statistical Heterogeneity
by: Firdaus, Muhammad, et al.
Published: (2024)
by: Firdaus, Muhammad, et al.
Published: (2024)
Owen Sampling Accelerates Contribution Estimation in Federated Learning
by: KhademSohi, Hossein, et al.
Published: (2025)
by: KhademSohi, Hossein, et al.
Published: (2025)
Heterogeneous Federated Learning via Personalized Generative Networks
by: Taghiyarrenani, Zahra, et al.
Published: (2023)
by: Taghiyarrenani, Zahra, et al.
Published: (2023)
Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation
by: Wei, Ting, et al.
Published: (2025)
by: Wei, Ting, et al.
Published: (2025)
Personalized Federated Learning with Exact Stochastic Gradient Descent
by: Nikoloutsopoulos, Sotirios, et al.
Published: (2022)
by: Nikoloutsopoulos, Sotirios, et al.
Published: (2022)
Separate Aggregation of Split Network for Personalized Federated Learning
by: Kang, Yunseok, et al.
Published: (2026)
by: Kang, Yunseok, et al.
Published: (2026)
Representation-Aligned Multi-Scale Personalization for Federated Learning
by: Liang, Wenfei, et al.
Published: (2026)
by: Liang, Wenfei, et al.
Published: (2026)
Personalized Federated Learning via Gaussian Generative Modeling
by: Hu, Peng, et al.
Published: (2026)
by: Hu, Peng, et al.
Published: (2026)
Personalized Federated Learning under Model Dissimilarity Constraints
by: Erickson, Samuel, et al.
Published: (2025)
by: Erickson, Samuel, et al.
Published: (2025)
Whom to Trust? Adaptive Collaboration in Personalized Federated Learning
by: Abourayya, Amr, et al.
Published: (2025)
by: Abourayya, Amr, et al.
Published: (2025)
IP-FL: Incentivized and Personalized Federated Learning
by: Khan, Ahmad Faraz, et al.
Published: (2023)
by: Khan, Ahmad Faraz, et al.
Published: (2023)
Personalized Multi-tier Federated Learning
by: Banerjee, Sourasekhar, et al.
Published: (2024)
by: Banerjee, Sourasekhar, et al.
Published: (2024)
Analytic Personalized Federated Meta-Learning
by: Gu, Shunxian, et al.
Published: (2025)
by: Gu, Shunxian, et al.
Published: (2025)
Graph Federated Learning for Personalized Privacy Recommendation
by: Na, Ce, et al.
Published: (2025)
by: Na, Ce, et al.
Published: (2025)
Curriculum Guided Personalized Subgraph Federated Learning
by: Kang, Minku, et al.
Published: (2025)
by: Kang, Minku, et al.
Published: (2025)
Federated Contrastive Learning for Personalized Semantic Communication
by: Wang, Yining, et al.
Published: (2024)
by: Wang, Yining, et al.
Published: (2024)
On Performance Guarantees for Federated Learning with Personalized Constraints
by: Ebrahimi, Mohammadjavad, et al.
Published: (2026)
by: Ebrahimi, Mohammadjavad, et al.
Published: (2026)
Similar Items
-
Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions
by: Zakerinia, Hossein, et al.
Published: (2025) -
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
by: Zakerinia, Hossein, et al.
Published: (2025) -
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms
by: Zakerinia, Hossein, et al.
Published: (2024) -
From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning
by: Zakerinia, Hossein, et al.
Published: (2025) -
From Privacy to Generalization: Linear Max-Information Bounds for DP-SGD
by: Lampert, Christoph H., et al.
Published: (2026)