Scalable coordinate descent approaches to parallel matrix factorization for recommender systems

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2012, Pages 765-774

  Yu, Hsiang Fu ^a   Hsieh, Cho Jui ^a   Si, Si ^a   Dhillon, Inderjit ^a  

^a University of Texas at Austin   (United States)

Author keywords

Low rank approximation; Matrix factorization; Parallelization; Recommender systems

Indexed keywords

ALTERNATING LEAST SQUARES; CLASSICAL OPTIMIZATION; COORDINATE DESCENT; DISTRIBUTED SYSTEMS; ITS APPLICATIONS; LARGE-SCALE DATASETS; LARGE-SCALE PROBLEM; LOW RANK APPROXIMATIONS; MATRIX FACTORIZATIONS; MISSING VALUES; MULTI CORE; PARALLELIZATIONS; SLOW CONVERGENCES; STABLE CONVERGENCE; STOCHASTIC GRADIENT DESCENT; TIME COMPLEXITY;

ALGORITHMS; DATA MINING;

RECOMMENDER SYSTEMS;

EID: 84874049380     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2012.168     Document Type: Conference Paper

References (20)

1. Y. Zhou, D. Wilkinson, R. Schreiber, and R. Pan, "Large-scale parallel collaborative filtering for the netflix prize," in Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management, 2008.
2. Y. Koren, R. M. Bell, and C. Volinsky, "Matrix factorization techniques for recommender systems," Computer, vol. 42, pp. 30-37, 2009.
3. G. Takács, I. Pilászy, B. Németh, and D. Tikk, "Scalable collaborative filtering approaches for large recommender systems," JMLR, vol. 10, pp. 623-656, 2009.
4. J. Langford, A. Smola, and M. Zinkevich, "Slow learners are fast," in NIPS, 2009.
5. R. Gemulla, P. J. Haas, E. Nijkamp, and Y. Sismanis, "Largescale matrix factorization with distributed stochastic gradient descent," in ACM KDD, 2011.
6. B. Recht, C. Re, and S. J. Wright, "Parallel stochastic gradient algorithms for large-scale matrix completion," 2011. Submitted for publication.
7. M. Zinkevich, M. Weimer, A. Smola, and L. Li, "Parallelized stochastic gradient descent," in NIPS, 2010.
8. F. Niu, B. Recht, C. Re, and S. J. Wright, "Hogwild!: A lockfree approach to parallelizing stochastic gradient descent," in NIPS, 2011.
9. A. Cichocki and A.-H. Phan, "Fast local algorithms for large scale nonnegative matrix and tensor factorizations," IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, vol. E92-A, no. 3, pp. 708-721, 2009.
10. C.-J. Hsieh and I. S. Dhillon, "Fast coordinate descent methods with variable selection for non-negative matrix factorization," in ACM KDD, 2011.
11. L. Bottou, "Large-scale machine learning with stochastic gradient descent," in Proceedings of the 19th International Conference on Computational Statistics, 2010.
12. A. Agarwal and J. C. Duchi, "Distributed delayed stochastic optimization," in NIPS 24, 2011.
13. D. P. Bertsekas, Nonlinear Programming. Belmont, MA 02178-9998: Athena Scientific, second ed., 1999.
14. C.-J. Hsieh, K.-W. Chang, C.-J. Lin, S. S. Keerthi, and S. Sundararajan, "A dual coordinate descent method for largescale linear SVM," in ICML, 2008.
15. H.-F. Yu, F.-L. Huang, and C.-J. Lin, "Dual coordinate descent methods for logistic regression and maximum entropy models," Machine Learning, vol. 85, pp. 41-75, October 2011.
16. C.-J. Hsieh, M. Sustik, I. S. Dhillon, and P. Ravikumar, "Sparse inverse covariance matrix estimation using quadratic approximation," in NIPS, 2011.
17. I. Pilászy, D. Zibriczky, and D. Tikk, "Fast ALS-based matrix factorization for explicit and implicit feedback datasets," in RecSys, 2010.
18. R. M. Bell, Y. Koren, and C. Volinsky, "Modeling relationships at multiple scales to improve accuracy of large recommender systems," in ACM KDD, 2007.
19. N.-D. Ho and P. V. D. V. D. Blondel, "Descent methods for nonnegative matrix factorization," in Numerical Linear Algebra in Signals, Systems and Control, pp. 251-293, Springer Netherlands, 2011.
20. Y. Low, J. Gonzalez, A. Kyrola, D. Bickson, C. Guestrin, and J. M. Hellerstein, "Distributed GraphLab: A framework for machine learning in the cloud," PVLDB, vol. 5, no. 8, pp. 716-727, 2012.