Interesting Papers

Here's an assortment of interesting papers from some of my colleagues in the recommendation/machine learning space that I've recently read.

• BPR: Bayesian Personalized Ranking from Implicit Feedback, Rendle et. al.
• Supercharging Recommender Systems using Taxonomies for Learning User Purchase Behavior, Kanagal et. al. in PVLDB 2012
• Latent factor models with additive and hierarchically-smoothed user preferences, Ahmed et. al. in WSDM 2013
• Matrix Approximation under Local Low-Rank Assumption, Joonseok Lee et. al. ICLR
• Sibyl: A system for large scale supervised machine learning