263 citations · 287 across the 2 of their papers we have counts for
2 papers
cs.LG2019★ 24 cited
Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology
Eugene Ie, Vihan Jain, Jing Wang +10
Most practical recommender systems focus on estimating immediate user engagement without considering the long-term effects of recommendations on user behavior. Reinforcement learni…
cs.LG2016★ 263 cited
Wide & Deep Learning for Recommender Systems
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen +13
Generalized linear models with nonlinear feature transformations are widely used for large-scale regression and classification problems with sparse inputs. Memorization of feature…