HeteRo-Select: Informativeness as the Participation Driver in Heterogeneous Federated Learning

arXiv:2508.06692 · cs.LG · Submitted 2026-08-18 · Read on arXiv

Md. Akmol Masud, Md Abrar Jahin, Mahmud Hasan

cs.LG

Submitted: 2026-08-18

Updated: 2026-08-19

Terminology

• Accuracy — 37× in this paper · explained in 1 episode
• Federated Learning — 30× in this paper · explained in 15 episodes
• Ablation — 17× in this paper · explained in 1 episode
• Aggregation — 15× in this paper · explained in 1 episode
• Non-IID Data — 10× in this paper · explained in 2 episodes
• Benchmark — 6× in this paper · explained in 2 episodes
• Allocator — 5× in this paper · explained in 1 episode
• International Conference on Learning Representations — 5× in this paper
• Quantization — 5× in this paper · explained in 12 episodes
• Regularization — 5× in this paper · explained in 3 episodes
• International Conference on Machine Learning — 4× in this paper
• Generalization — 3× in this paper · explained in 13 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Clustering — 1× in this paper · explained in 2 episodes
• Computer Vision and Pattern Recognition — 1× in this paper
• Federated Learning (FL) — 1× in this paper · explained in 7 episodes
• Model-Agnostic — 1× in this paper · explained in 2 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Theoretical Guarantees — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Federated Learning: Strategies for Improving Communication Efficiency
• Client Selection in Federated Learning: Convergence Analysis and Power-of-Choice Selection Strategies
• FedSTaS: Client Stratification and Client Level Sampling for Efficient Federated Learning
• Optimal Client Sampling for Federated Learning
• Emulating Full Participation: An Effective and Fair Client Selection Strategy for Federated Learning
• Mechanistic Evidence for Preserved-but-Misaligned Representations in Non-IID FedAvg

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks