43 citations · 49 across the 21 of their papers we have counts for
3 papers · 1 filter
CB2CF: A Neural Multiview Content-to-Collaborative Filtering Model for Completely Cold Item Recommendations
Oren Barkan, Noam Koenigstein, Eylon Yogev +1
In Recommender Systems research, algorithms are often characterized as either Collaborative Filtering (CF) or Content Based (CB). CF algorithms are trained using a dataset of user…
The Bayesian Low-Rank Determinantal Point Process Mixture Model
Mike Gartrell, Ulrich Paquet, Noam Koenigstein
Determinantal point processes (DPPs) are an elegant model for encoding probabilities over subsets, such as shopping baskets, of a ground set, such as an item catalog. They are usef…
Low-Rank Factorization of Determinantal Point Processes for Recommendation
Mike Gartrell, Ulrich Paquet, Noam Koenigstein
Determinantal point processes (DPPs) have garnered attention as an elegant probabilistic model of set diversity. They are useful for a number of subset selection tasks, including p…