Rectifying Geometric Misalignment: Online Source-Free Adaptation for Class-Imbalanced EEG

arXiv:2608.05315 · cs.LG · Submitted 2026-08-05 · Read on arXiv

Shiwen Chu, Shanglin Li, Motoaki Kawanabe, Reinmar Kobler

cs.LG

Submitted: 2026-08-05

Comments: Accepted at EUSIPCO 2026

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Domain Adaptation — 15× in this paper · explained in 5 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Class Imbalance — 5× in this paper · explained in 3 episodes
• Covariate Shift — 5× in this paper · explained in 3 episodes
• Online Adaptation — 5× in this paper · explained in 3 episodes
• Transfer Learning — 5× in this paper · explained in 16 episodes
• Calibration — 3× in this paper · explained in 9 episodes
• Distribution Shift — 3× in this paper · explained in 12 episodes
• Distribution Shifts — 3× in this paper · explained in 2 episodes
• Domain Shift — 3× in this paper · explained in 7 episodes
• Riemannian Centering Transformation — 3× in this paper
• Generalization — 2× in this paper · explained in 14 episodes
• Performance Gap — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation Study — 1× in this paper · explained in 3 episodes
• Adam — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cross-Domain Generalization — 1× in this paper · explained in 3 episodes
• Decoder — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Non-stationarity — 1× in this paper · explained in 2 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Semantic Segmentation — 1× in this paper · explained in 3 episodes

Sources

• HEEGNet: Hyperbolic Embeddings for EEG
• Deep Optimal Transport for Domain Adaptation on SPD Manifolds
• Geodesic Optimization for Predictive Shift Adaptation on EEG data
• Latent Alignment with Deep Set EEG Decoders

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