22 citations · 25 across the 7 of their papers we have counts for
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cs.IR2025
A Geometric Approach to Personalized Recommendation with Set-Theoretic Constraints Using Box Embeddings
Shib Dasgupta, Michael Boratko, Andrew McCallum
Personalized item recommendation typically suffers from data sparsity, which is most often addressed by learning vector representations of users and items via low-rank matrix facto…
cs.IR2023
Answering Compositional Queries with Set-Theoretic Embeddings
Shib Dasgupta, Andrew McCallum, Steffen Rendle +1
The need to compactly and robustly represent item-attribute relations arises in many important tasks, such as faceted browsing and recommendation systems. A popular machine learnin…