#Federated Learning
Latest news articles tagged with "Federated Learning". Follow the timeline of events, related topics, and entities.
Articles (23)
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🇺🇸 FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients
[USA]
arXiv:2603.19722v1 Announce Type: cross Abstract: Federated learning (FL) suffers from performance degradation due to the inevitable presence of noisy annotations in distributed scenarios. Existing a...
Related: #Machine Learning -
🇺🇸 QuantFL: Sustainable Federated Learning for Edge IoT via Pre-Trained Model Quantisation
[USA]
arXiv:2603.17507v1 Announce Type: cross Abstract: Federated Learning (FL) enables privacy-preserving intelligence on Internet of Things (IoT) devices but incurs a significant carbon footprint due to ...
Related: #Edge IoT, #Model Quantization -
🇺🇸 FedUAF: Uncertainty-Aware Fusion with Reliability-Guided Aggregation for Multimodal Federated Sentiment Analysis
[USA]
arXiv:2603.13291v1 Announce Type: cross Abstract: Multimodal sentiment analysis in federated learning environments faces significant challenges due to missing modalities, heterogeneous data distribut...
Related: #Sentiment Analysis -
🇺🇸 A Robust Framework for Secure Cardiovascular Risk Prediction: An Architectural Case Study of Differentially Private Federated Learning
[USA]
arXiv:2603.13293v1 Announce Type: cross Abstract: Accurate cardiovascular risk prediction is crucial for preventive healthcare; however, the development of robust Artificial Intelligence (AI) models ...
Related: #Healthcare AI, #Data Privacy -
🇺🇸 FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning
[USA]
arXiv:2603.13282v1 Announce Type: cross Abstract: Federated Learning (FL) with Low-Rank Adaptation (LoRA) has become a standard for privacy-preserving LLM fine-tuning. However, existing personalized ...
Related: #Model Fine-Tuning -
🇺🇸 FedBPrompt: Federated Domain Generalization Person Re-Identification via Body Distribution Aware Visual Prompts
[USA]
arXiv:2603.12912v1 Announce Type: cross Abstract: Federated Domain Generalization for Person Re-Identification (FedDG-ReID) learns domain-invariant representations from decentralized data. While Visi...
Related: #Computer Vision -
🇺🇸 CA-HFP: Curvature-Aware Heterogeneous Federated Pruning with Model Reconstruction
[USA]
arXiv:2603.12591v1 Announce Type: cross Abstract: Federated learning on heterogeneous edge devices requires personalized compression while preserving aggregation compatibility and stable convergence....
Related: #Model Optimization -
🇺🇸 Federated Hierarchical Clustering with Automatic Selection of Optimal Cluster Numbers
[USA]
arXiv:2603.12684v1 Announce Type: cross Abstract: Federated Clustering (FC) is an emerging and promising solution in exploring data distribution patterns from distributed and privacy-protected data i...
Related: #Data Privacy, #Machine Learning -
🇺🇸 Repurposing Backdoors for Good: Ephemeral Intrinsic Proofs for Verifiable Aggregation in Cross-silo Federated Learning
[USA]
arXiv:2603.10692v1 Announce Type: cross Abstract: While Secure Aggregation (SA) protects update confidentiality in Cross-silo Federated Learning, it fails to guarantee aggregation integrity, allowing...
Related: #Cybersecurity, #Data Privacy -
🇺🇸 Benchmarking Federated Learning in Edge Computing Environments: A Systematic Review and Performance Evaluation
[USA]
arXiv:2603.08735v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as a transformative approach for distributed machine learning, particularly in edge computing environments where ...
Related: #Edge Computing -
🇺🇸 FedLECC: Cluster- and Loss-Guided Client Selection for Federated Learning under Non-IID Data
[USA]
arXiv:2603.08911v1 Announce Type: cross Abstract: Federated Learning (FL) enables distributed Artificial Intelligence (AI) across cloud-edge environments by allowing collaborative model training with...
Related: #Machine Learning Optimization -
🇺🇸 Trust Aware Federated Learning for Secure Bone Healing Stage Interpretation in e-Health
[USA]
arXiv:2603.06646v1 Announce Type: cross Abstract: This paper presents a trust aware federated learning (FL) framework for interpreting bone healing stages using spectral features derived from frequen...
Related: #e-Health Security -
🇺🇸 Federated Causal Discovery Across Heterogeneous Datasets under Latent Confounding
[USA]
arXiv:2603.05149v1 Announce Type: cross Abstract: Causal discovery across multiple datasets is often constrained by data privacy regulations and cross-site heterogeneity, limiting the use of conventi...
Related: #Causal Discovery, #Data Privacy -
🇺🇸 FedEMA-Distill: Exponential Moving Average Guided Knowledge Distillation for Robust Federated Learning
[USA]
arXiv:2603.04422v1 Announce Type: cross Abstract: Federated learning (FL) often degrades when clients hold heterogeneous non-Independent and Identically Distributed (non-IID) data and when some clien...
Related: #Machine Learning -
🇺🇸 ZorBA: Zeroth-order Federated Fine-tuning of LLMs with Heterogeneous Block Activation
[USA]
arXiv:2603.04436v1 Announce Type: cross Abstract: Federated fine-tuning of large language models (LLMs) enables collaborative tuning across distributed clients. However, due to the large size of LLMs...
Related: #LLM Optimization -
🇺🇸 FedAFD: Multimodal Federated Learning via Adversarial Fusion and Distillation
[USA]
arXiv:2603.04890v1 Announce Type: cross Abstract: Multimodal Federated Learning (MFL) enables clients with heterogeneous data modalities to collaboratively train models without sharing raw data, offe...
Related: #Multimodal AI -
🇺🇸 FedBCD:Communication-Efficient Accelerated Block Coordinate Gradient Descent for Federated Learning
[USA]
arXiv:2603.05116v1 Announce Type: cross Abstract: Although Federated Learning has been widely studied in recent years, there are still high overhead expenses in each communication round for large-sca...
Related: #Optimization Algorithms -
🇺🇸 FedDAG: Clustered Federated Learning via Global Data and Gradient Integration for Heterogeneous Environments
[USA]
arXiv:2602.23504v1 Announce Type: cross Abstract: Federated Learning (FL) enables a group of clients to collaboratively train a model without sharing individual data, but its performance drops when c...
Related: #Client Data Heterogeneity, #Clustered Federated Learning, #Cross‑cluster Knowledge Transfer, #Gradient‑Based Similarity -
🇺🇸 Wireless Federated Multi-Task LLM Fine-Tuning via Sparse-and-Orthogonal LoRA
[USA]
arXiv:2602.20492v1 Announce Type: cross Abstract: Decentralized federated learning (DFL) based on low-rank adaptation (LoRA) enables mobile devices with multi-task datasets to collaboratively fine-tu...
Related: #Machine Learning, #Wireless Technology, #Natural Language Processing -
🇺🇸 FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment
[USA]
arXiv:2602.17095v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning techniques such as low-rank adaptation (LoRA) enable large language models (LLMs) to adapt to downstream tasks effici...
Related: #Parameter‑Efficient Fine‑Tuning, #Low‑Rank Adaptation, #Communication Efficiency, #Theoretical Convergence Analysis -
🇺🇸 FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels
[USA]
arXiv:2504.05615v3 Announce Type: replace-cross Abstract: Federated Learning (FL) is a powerful framework for privacy-preserving distributed learning. It enables multiple clients to collaboratively t...
Related: #Robustness to Noisy Labels, #Forward Correction Techniques, #Privacy‑Preserving Distributed Training, #Communication Efficiency in FL -
🇺🇸 Hybrid Federated and Split Learning for Privacy Preserving Clinical Prediction and Treatment Optimization
[USA]
arXiv:2602.15304v1 Announce Type: cross Abstract: Collaborative clinical decision support is often constrained by governance and privacy rules that prevent pooling patient-level records across instit...
Related: #Data Privacy, #Collaborative Machine Learning, #Medical AI, #Split Learning -
🇺🇸 SCENE OTA-FD: Self-Centering Noncoherent Estimator for Over-the-Air Federated Distillation
[USA]
arXiv:2602.15326v1 Announce Type: cross Abstract: We propose SCENE (Self-Centering Noncoherent Estimator), a pilot-free and phase-invariant aggregation primitive for over-the-air federated distillati...
Related: #Over‑the‑Air Communication, #Signal Processing, #Energy‑Based Estimation, #Pilot‑Free Techniques
Key Entities (5)
- Performance Evaluation (1 news)
- Systematic review (1 news)
- LoRA (machine learning) (1 news)
- Wireless (1 news)
- Large language model (1 news)
About the topic: Federated Learning
The topic "Federated Learning" aggregates 23+ news articles from various countries.