Saved in:
| Main Authors: | Kim, Yeongwoo, Hakim, Ezeddin Al, Haraldson, Johan, Eriksson, Henrik, Silva Jr., José Mairton B. da, Fischione, Carlo |
|---|---|
| Format: | Preprint |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2012.03788 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Blind Federated Learning via Over-the-Air q-QAM
by: Razavikia, Saeed, et al.
Published: (2023)
by: Razavikia, Saeed, et al.
Published: (2023)
Federated Learning Using Three-Operator ADMM
by: Kant, Shashi, et al.
Published: (2022)
by: Kant, Shashi, et al.
Published: (2022)
FedCau: A Proactive Stop Policy for Communication and Computation Efficient Federated Learning
by: Mahmoudi, Afsaneh, et al.
Published: (2022)
by: Mahmoudi, Afsaneh, et al.
Published: (2022)
VecComp: Vector Computing via MIMO Digital Over-the-Air Computation
by: Razavikia, Saeed, et al.
Published: (2025)
by: Razavikia, Saeed, et al.
Published: (2025)
VR-VFL: Joint Rate and Client Selection for Vehicular Federated Learning Under Imperfect CSI
by: Karatas, Metehan, et al.
Published: (2026)
by: Karatas, Metehan, et al.
Published: (2026)
Decentralized Fairness Aware Multi Task Federated Learning for VR Network
by: Tharakan, Krishnendu S., et al.
Published: (2025)
by: Tharakan, Krishnendu S., et al.
Published: (2025)
A Generalized Hierarchical Federated Learning Framework with Theoretical Guarantees
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2025)
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2025)
Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2025)
by: Azimi-Abarghouyi, Seyed Mohammad, et al.
Published: (2025)
SumComp: Coding for Digital Over-the-Air Computation via the Ring of Integers
by: Razavikia, Saeed, et al.
Published: (2023)
by: Razavikia, Saeed, et al.
Published: (2023)
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning
by: Song, Yeongwoo, et al.
Published: (2022)
by: Song, Yeongwoo, et al.
Published: (2022)
Hierarchical Federated Learning with SignSGD: A Highly Communication-Efficient Approach
by: Kazemi, Amirreza, et al.
Published: (2026)
by: Kazemi, Amirreza, et al.
Published: (2026)
Machine Learning for Spectrum Sharing: A Survey
by: Guimarães, Francisco R. V., et al.
Published: (2024)
by: Guimarães, Francisco R. V., et al.
Published: (2024)
Uncovering Emergent Physics Representations Learned In-Context by Large Language Models
by: Song, Yeongwoo, et al.
Published: (2025)
by: Song, Yeongwoo, et al.
Published: (2025)
Stochastic Resetting Mitigates Latent Gradient Bias of SGD from Label Noise
by: Bae, Youngkyoung, et al.
Published: (2024)
by: Bae, Youngkyoung, et al.
Published: (2024)
Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy
by: Schönbauer, Sita, et al.
Published: (2025)
by: Schönbauer, Sita, et al.
Published: (2025)
Dynamic Clustering for Personalized Federated Learning on Heterogeneous Edge Devices
by: Liu, Heting, et al.
Published: (2025)
by: Liu, Heting, et al.
Published: (2025)
Language-Assisted Feature Transformation for Anomaly Detection
by: Yun, EungGu, et al.
Published: (2025)
by: Yun, EungGu, et al.
Published: (2025)
FedDAA: Dynamic Client Clustering for Concept Drift Adaptation in Federated Learning
by: Peng, Fu, et al.
Published: (2025)
by: Peng, Fu, et al.
Published: (2025)
Marginal Pseudo-Likelihood Learning of Markov Network structures
by: Pensar, Johan, et al.
Published: (2014)
by: Pensar, Johan, et al.
Published: (2014)
Decoupled Subgraph Federated Learning
by: Aliakbari, Javad, et al.
Published: (2024)
by: Aliakbari, Javad, et al.
Published: (2024)
Optimizing Communication and Device Clustering for Clustered Federated Learning with Differential Privacy
by: Wei, Dongyu, et al.
Published: (2025)
by: Wei, Dongyu, et al.
Published: (2025)
Comparative Evaluation of Clustered Federated Learning Methods
by: Ali, Michael Ben, et al.
Published: (2024)
by: Ali, Michael Ben, et al.
Published: (2024)
Clustered Federated Learning via Embedding Distributions
by: Zhang, Dekai, et al.
Published: (2025)
by: Zhang, Dekai, et al.
Published: (2025)
MoCFL: Mobile Cluster Federated Learning Framework for Highly Dynamic Network
by: Fang, Kai, et al.
Published: (2025)
by: Fang, Kai, et al.
Published: (2025)
Cluster Specific Representation Learning
by: Sabanayagam, Mahalakshmi, et al.
Published: (2024)
by: Sabanayagam, Mahalakshmi, et al.
Published: (2024)
The Fairness-Quality Trade-off in Clustering
by: Hakim, Rashida, et al.
Published: (2024)
by: Hakim, Rashida, et al.
Published: (2024)
Empowering HWNs with Efficient Data Labeling: A Clustered Federated Semi-Supervised Learning Approach
by: Hamood, Moqbel, et al.
Published: (2024)
by: Hamood, Moqbel, et al.
Published: (2024)
Achieving Linear Speedup for Composite Federated Learning
by: Huang, Kun, et al.
Published: (2026)
by: Huang, Kun, et al.
Published: (2026)
One-Shot Clustering for Federated Learning
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
Personalized Federated Learning for Cellular VR: Online Learning and Dynamic Caching
by: Tharakan, Krishnendu S., et al.
Published: (2025)
by: Tharakan, Krishnendu S., et al.
Published: (2025)
Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation
by: Wang, Jiaqi, et al.
Published: (2024)
by: Wang, Jiaqi, et al.
Published: (2024)
Fed-BAC: Federated Bandit-Guided Additive Clustering in Hierarchical Federated Learning
by: Bashir, Satwat, et al.
Published: (2026)
by: Bashir, Satwat, et al.
Published: (2026)
Differentially Private Federated Clustering with Random Rebalancing
by: Yang, Xiyuan, et al.
Published: (2025)
by: Yang, Xiyuan, et al.
Published: (2025)
Interaction-Aware Gaussian Weighting for Clustered Federated Learning
by: Licciardi, Alessandro, et al.
Published: (2025)
by: Licciardi, Alessandro, et al.
Published: (2025)
Federated Learning with Multi-resolution Model Broadcast
by: Rydén, Henrik, et al.
Published: (2024)
by: Rydén, Henrik, et al.
Published: (2024)
An Equal-Probability Partition of the Sample Space: A Non-parametric Inference from Finite Samples
by: Eriksson, Urban
Published: (2025)
by: Eriksson, Urban
Published: (2025)
Relaxed Contrastive Learning for Federated Learning
by: Seo, Seonguk, et al.
Published: (2024)
by: Seo, Seonguk, et al.
Published: (2024)
FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling
by: Chen, Cheng, et al.
Published: (2020)
by: Chen, Cheng, et al.
Published: (2020)
One-Shot Clustering for Federated Learning Under Clustering-Agnostic Assumption
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
by: Zuziak, Maciej Krzysztof, et al.
Published: (2025)
CCFC: Bridging Federated Clustering and Contrastive Learning
by: Liu, Jing, et al.
Published: (2024)
by: Liu, Jing, et al.
Published: (2024)
Similar Items
-
Blind Federated Learning via Over-the-Air q-QAM
by: Razavikia, Saeed, et al.
Published: (2023) -
Federated Learning Using Three-Operator ADMM
by: Kant, Shashi, et al.
Published: (2022) -
FedCau: A Proactive Stop Policy for Communication and Computation Efficient Federated Learning
by: Mahmoudi, Afsaneh, et al.
Published: (2022) -
VecComp: Vector Computing via MIMO Digital Over-the-Air Computation
by: Razavikia, Saeed, et al.
Published: (2025) -
VR-VFL: Joint Rate and Client Selection for Vehicular Federated Learning Under Imperfect CSI
by: Karatas, Metehan, et al.
Published: (2026)