SCOPE: Scalable Training-Free Semantic Coreset Selection for Long-Tailed Federated Learning

arXiv:2603.12976 · cs.LG, cs.CV · Submitted 2026-03-13 · Read on arXiv

cs.LG, cs.CV

Submitted: 2026-03-13

Updated: 2026-10-20

Terminology

• Class Imbalance — 2× in this paper · explained in 2 episodes
• Federated Learning — 2× in this paper · explained in 17 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Pruning — 1× in this paper · explained in 4 episodes

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: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks