GeoDM: Geometry-aware Distribution Matching for Dataset Distillation
Published:Dec 9, 2025 07:31
•1 min read
•ArXiv
Analysis
The article introduces GeoDM, a method for dataset distillation that considers geometric properties. The focus is on improving the efficiency and effectiveness of distilling datasets, likely for applications in machine learning model training. The use of 'geometry-aware' suggests a novel approach to the problem.
Key Takeaways
- •GeoDM is a new method for dataset distillation.
- •It incorporates geometric information.
- •The goal is to improve efficiency and effectiveness of dataset distillation.
Reference
“”