SpecGradFilter: A Spectral Gradient Filtering Framework for Taming Federated Heterogeneity

arXiv:2607.04189 · cs.LG · Submitted 2026-07-05 · Read on arXiv

cs.LG

Submitted: 2026-07-05

Updated: 2026-08-28

Terminology

• Federated Learning — 46× in this paper · explained in 15 episodes
• Accuracy — 34× in this paper · explained in 1 episode
• Aggregation — 13× in this paper · explained in 1 episode
• Robustness — 11× in this paper · explained in 5 episodes
• Data Heterogeneity — 10× in this paper · explained in 3 episodes
• Regularization — 10× in this paper · explained in 3 episodes
• Alignment — 9× in this paper · explained in 1 episode
• Generalization — 8× in this paper · explained in 13 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Non-IID Data — 5× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Core — 3× in this paper · explained in 2 episodes
• Federated Learning (FL) — 3× in this paper · explained in 7 episodes
• Local Optimization — 3× in this paper · explained in 2 episodes
• Communication Overhead — 2× in this paper · explained in 2 episodes
• Computational overhead — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Gaussian Detrend — 2× in this paper
• AI Agents — 1× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Centered Kernel Alignment — 1× in this paper
• Centered Kernel Alignment (CKA) — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Decoupling — 1× in this paper · explained in 2 episodes
• Differential Privacy — 1× in this paper · explained in 4 episodes
• Distribution Shift — 1× in this paper · explained in 6 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• High-Energy Concentration for Federated Learning in Frequency Domain
• FedFT: Improving Communication Performance for Federated Learning with Frequency Space Transformation
• LEAF: A Benchmark for Federated Settings

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