← Applications
Data Science & Analytics › Applications ›

Recommender Systems

1012 directly classified papers

Papers per year

Papers

Linear Submodular Bandits and their Application to Diversified Retrieval NIPS 2011
Divide-and-Conquer Matrix Factorization NIPS 2011
RTRMC: A Riemannian trust-region method for low-rank matrix completion NIPS 2011
A Collaborative Mechanism for Crowdsourcing Prediction Problems NIPS 2011
A Denoising View of Matrix Completion NIPS 2011
A Machine Learning Approach to Predict Chemical Reactions NIPS 2011
Iterative Learning for Reliable Crowdsourcing Systems NIPS 2011
Randomized Algorithms for Comparison-based Search NIPS 2011
Efficient Online Learning via Randomized Rounding NIPS 2011
Estimating Probabilities in Recommendation Systems AISTATS 2011
Collaborative Filtering with the Trace Norm: Learning, Bounding, and Transducing COLT 2011
Non-Stochastic Bandit Slate Problems NIPS 2010
Multi-task Learning for Recommender System ACML 2010
Collaborative Filtering via Rating Concentration AISTATS 2010
Gaussian Process Preference Elicitation NIPS 2010
Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets NIPS 2010
Collaborative Filtering on a Budget AISTATS 2010
A New Probabilistic Model for Rank Aggregation NIPS 2010
Collaborative Filtering in a Non-Uniform World: Learning with the Weighted Trace Norm NIPS 2010
On the Convexity of Latent Social Network Inference NIPS 2010
Factor Modeling for Advertisement Targeting NIPS 2009
Scalable Collaborative Filtering Approaches for Large Recommender Systems JMLR 2009
A Survey of Accuracy Evaluation Metrics of Recommendation Tasks JMLR 2009
Matrix Completion from Noisy Entries NIPS 2009
A Data-Driven Approach to Modeling Choice NIPS 2009