·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Meta-ethics and AI: exploring the novel meta-ethical questions in the era of AI2h◆SSAKG 2.0: An Open-Source Package for Structural Associative Sequence Memory and Context-Based Retrieval2h◆Epistemic Sybil Resistance: Multiplying AI Agents Without Multiplying Evidence2h◆DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents2h◆MASkills: Continual Skills Optimization for Multi-Agent LLM Systems2h◆Train at Moving Edge: Online-Verified Prompt Selection for Efficient RL Training of Large Reasoning Model2h◆SpecMine: A Large-Scale Corpus of Spec-Driven Development Artifacts2h◆Elite political incivility is rising across democracies2h◆Learning Query-Specific Rubrics from Human Preferences for DeepResearch Report Generation2h◆Sim2Signal: Sim-to-Real Benchmarks for Traffic Signal Control2h◆Recursive Value Learning for Long-Horizon Offline Goal-Conditioned RL2h◆Similarity-Aware Personalized Federated Learning in Heterogeneous Environments2h◆Oracle, will I ever learn? A study of prediction convergence and complementarity across link prediction models2h◆UE5M3 FP4 Block Scaling for Stable Language Model Pretraining2h◆Network-Aware Forecasting on Wireless Access Points2h◆Monotonic anomaly detection2h◆Cantelli Constrained Policy Optimization2h◆Secure AI-Driven Super-Resolution for Real-Time Mixed Reality Applications2h◆From Digital to Physical Reservoir Computing: Co-Optimizing Soft Robotic Reservoirs via Dynamics Matching2h◆Optimal Transport for Network Comparison: A Review with Machine Learning Applications2h◆Meta-ethics and AI: exploring the novel meta-ethical questions in the era of AI2h◆SSAKG 2.0: An Open-Source Package for Structural Associative Sequence Memory and Context-Based Retrieval2h◆Epistemic Sybil Resistance: Multiplying AI Agents Without Multiplying Evidence2h◆DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents2h◆MASkills: Continual Skills Optimization for Multi-Agent LLM Systems2h◆Train at Moving Edge: Online-Verified Prompt Selection for Efficient RL Training of Large Reasoning Model2h◆SpecMine: A Large-Scale Corpus of Spec-Driven Development Artifacts2h◆Elite political incivility is rising across democracies2h◆Learning Query-Specific Rubrics from Human Preferences for DeepResearch Report Generation2h◆Sim2Signal: Sim-to-Real Benchmarks for Traffic Signal Control2h◆Recursive Value Learning for Long-Horizon Offline Goal-Conditioned RL2h◆Similarity-Aware Personalized Federated Learning in Heterogeneous Environments2h◆Oracle, will I ever learn? A study of prediction convergence and complementarity across link prediction models2h◆UE5M3 FP4 Block Scaling for Stable Language Model Pretraining2h◆Network-Aware Forecasting on Wireless Access Points2h◆Monotonic anomaly detection2h◆Cantelli Constrained Policy Optimization2h◆Secure AI-Driven Super-Resolution for Real-Time Mixed Reality Applications2h◆From Digital to Physical Reservoir Computing: Co-Optimizing Soft Robotic Reservoirs via Dynamics Matching2h◆Optimal Transport for Network Comparison: A Review with Machine Learning Applications2h◆
News/Similarity-Aware Personalized Federated Learning in Heterogeneous Environments
arxiv
PublishedSeptember 3, 2026 at 4:00 AM
—neutral

Similarity-Aware Personalized Federated Learning in Heterogeneous Environments

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2609.02241v1 Announce Type: new Abstract: Federated Learning (FL) allows decentralized clients to train models collaboratively while preserving data privacy. However, distribution mismatch across clients often leads to poor global generalization and degraded local client-level performance. In

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivMeta-ethics and AI: exploring the novel meta-ethical questions in the era of AI2harxivSSAKG 2.0: An Open-Source Package for Structural Associative Sequence Memory and Context-Based Retrieval2harxivEpistemic Sybil Resistance: Multiplying AI Agents Without Multiplying Evidence2harxivDocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents2h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews