A gradient-alignment influence score (GGscore) that selects the highest- and lowest-scoring old interactions for replay improves incremental neural recommendation slightly over random replay, mainly at large replay ratios.
In: Proceedings of the 2nd Interna- tional Workshop on Deep Multimodal Gener- ation and Retrieval
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MEGG: Replay via Maximally Extreme GGscore in Incremental Learning for Neural Recommendation Models
A gradient-alignment influence score (GGscore) that selects the highest- and lowest-scoring old interactions for replay improves incremental neural recommendation slightly over random replay, mainly at large replay ratios.