Dataset Condensation for Recommendation

Understand

Training recommendation models on large datasets requires significant time and resources.

• It is desired to construct concise yet informative datasets for efficient training.
• Recent advances in dataset condensation show promise in addressing this problem by synthesizing small datasets.
• However, applying existing methods of dataset condensation to recommendation has limitations: (1) they fail to generate discrete user-item interactions, and (2) they could not preserve users' potential preferences.