EEG-DLite: Dataset Distillation Streamlines Large EEG Model Training

This research introduces a method for more efficient training of large EEG models using dataset distillation. The work potentially reduces computational costs and accelerates development in the field of EEG analysis.

• •Focuses on improving the efficiency of training large EEG models.
• •Utilizes dataset distillation, suggesting a potential for reduced computational resources.
• •Targets improvements in EEG analysis, offering advances in brain-computer interfaces or medical diagnostics.