A finite algorithm for finding the projection of a point onto the Canonical simplex of Rn
Journal of Optimization Theory and Applications
Collaborative filtering with privacy via factor analysis
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Privacy-Preserving Collaborative Filtering Using Randomized Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
PocketLens: Toward a personal recommender system
ACM Transactions on Information Systems (TOIS)
Distributed collaborative filtering for peer-to-peer file sharing systems
Proceedings of the 2006 ACM symposium on Applied computing
Private distributed collaborative filtering using estimated concordance measures
Proceedings of the 2007 ACM conference on Recommender systems
A decentralized algorithm for spectral analysis
Journal of Computer and System Sciences
Scalable Collaborative Filtering with Jointly Derived Neighborhood Interpolation Weights
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
A peer-to-peer recommender system based on spontaneous affinities
ACM Transactions on Internet Technology (TOIT)
Collaborative filtering with temporal dynamics
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Scalable Collaborative Filtering Approaches for Large Recommender Systems
The Journal of Machine Learning Research
Exact Matrix Completion via Convex Optimization
Foundations of Computational Mathematics
Personalized communities in a distributed recommender system
ECIR'07 Proceedings of the 29th European conference on IR research
The power of convex relaxation: near-optimal matrix completion
IEEE Transactions on Information Theory
Matrix Completion from Noisy Entries
The Journal of Machine Learning Research
Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems
SCAMPI: service platform for social aware mobile and pervasive computing
Proceedings of the first edition of the MCC workshop on Mobile cloud computing
Crowdsourcing recommendations from social sentiment
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
SCAMPI: service platform for social aware mobile and pervasive computing
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
Privacy and coordination: computing on databases with endogenous participation
Proceedings of the fourteenth ACM conference on Electronic commerce
Proceedings of the 22nd international conference on World Wide Web companion
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Recommender systems predict user preferences based on a range of available information. For systems in which users generate streams of content (e.g., blogs, periodically-updated newsfeeds), users may rate the produced content that they read, and be given accurate predictions about future content they are most likely to prefer. We design a distributed mechanism for predicting user ratings that avoids the disclosure of information to a centralized authority or an untrusted third party: users disclose the rating they give to certain content only to the user that produced this content. We demonstrate how rating prediction in this context can be formulated as a matrix factorization problem. Using this intuition, we propose a distributed gradient descent algorithm for its solution that abides with the above restriction on how information is exchanged between users. We formally analyse the convergence properties of this algorithm, showing that it reduces a weighted root mean square error of the accuracy of predictions. Although our algorithm may be used many different ways, we evaluate it on the Neflix data set and prediction problem as a benchmark. In addition to the improved privacy properties that stem from its distributed nature, our algorithm is competitive with current centralized solutions. Finally, we demonstrate the algorithm's fast convergence in practice by conducting an online experiment with a prototype user-generated content exchange system implemented as a Facebook application.