Modeling item-item similarities for personalized recommendations on Yahoo! front page

DOI10.1214/11-AOAS475zbMath1231.62207arXiv1111.0416OpenAlexW3103968308MaRDI QIDQ652346

Deepak Agarwal, Rahul Mazumder, Liang Zhang

Publication date: 14 December 2011

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1111.0416

zbMATH Keywords

matrix factorizationcollaborative filteringrecommender systemsgraphical lassoitem-item similarities

Mathematics Subject Classification ID

Related Items (6)

Unnamed Item ⋮ Graph link prediction in computer networks using Poisson matrix factorisation ⋮ Bayesian hierarchical rule modeling for predicting medical conditions ⋮ Flexible low-rank statistical modeling with missing data and side information ⋮ Main effects and interactions in mixed and incomplete data frames ⋮ Unnamed Item

Uses Software

• S-PLUS
• LIBLINEAR
• glasso
• ElemStatLearn
• MEMSS

Cites Work

• Sparse inverse covariance estimation with the graphical lasso
• Asymptotically efficient adaptive allocation rules
• One-armed bandit problems with covariates
• Construction of high-order deceptive functions using low-order Walsh coefficients
• Optimal scaling for various Metropolis-Hastings algorithms.
• Randomized allocation with nonparametric estimation for a multi-armed bandit problem with covariates
• Arbitrary side observations in bandit problems
• High-dimensional graphs and variable selection with the Lasso
• Mixed-Effects Models in S and S-PLUS
• Approximate Inference in Generalized Linear Mixed Models
• Methods of conjugate gradients for solving linear systems
• Finite-time analysis of the multiarmed bandit problem
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