-
1
-
-
84916537550
-
Bayesian analysis of binary and polychotomous response data
-
Albert, J. H., Chib, S.: Bayesian analysis of binary and polychotomous response data. J. Am. Stat. Assoc. 88(422), 669-679 (1993).
-
(1993)
J. Am. Stat. Assoc.
, vol.88
, Issue.422
, pp. 669-679
-
-
Albert, J.H.1
Chib, S.2
-
2
-
-
0034337187
-
Internet recommendation systems
-
Ansari, A., Essegaier, S., Kohli, R.: Internet recommendation systems. J. Mark. Res., 363-375 (2000).
-
(2000)
J. Mark. Res
, pp. 363-375
-
-
Ansari, A.1
Essegaier, S.2
Kohli, R.3
-
4
-
-
57049165370
-
-
Tech. rep., AT& T Labs-Research
-
Bell, R. M., Koren, Y., Volinsky, C.: The BellKor solution to the Netflix prize. Tech. rep., AT& T Labs-Research (2007).
-
(2007)
The BellKor solution to the Netflix prize
-
-
Bell, R.M.1
Koren, Y.2
Volinsky, C.3
-
5
-
-
34547198396
-
Algorithms and applications for approximate nonnegative matrix factorization
-
Berry, M. W., Browne, M., Langville, A. N., Pauca, V. P., Plemmons, R. J.: Algorithms and applications for approximate nonnegative matrix factorization. Comput. Stat. Data Anal. 52(1), 155-173 (2007).
-
(2007)
Comput. Stat. Data Anal.
, vol.52
, Issue.1
, pp. 155-173
-
-
Berry, M.W.1
Browne, M.2
Langville, A.N.3
Pauca, V.P.4
Plemmons, R.J.5
-
6
-
-
21844453228
-
Gaussian processes for ordinal regression
-
Chu, W., Ghahramani, Z.: Gaussian processes for ordinal regression. J. Mach. Learn. Res. 6, 1019-1041 (2005).
-
(2005)
J. Mach. Learn. Res.
, vol.6
, pp. 1019-1041
-
-
Chu, W.1
Ghahramani, Z.2
-
7
-
-
0021518209
-
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
-
Geman, S., Geman, D.: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Trans. Pattern Anal. Mach. Intell. 6, 721-741 (1984).
-
(1984)
IEEE Trans. Pattern Anal. Mach. Intell.
, vol.6
, pp. 721-741
-
-
Geman, S.1
Geman, D.2
-
9
-
-
0033225865
-
An introduction to variational methods for graphical models
-
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., Saul, L. K.: An introduction to variational methods for graphical models. Mach. Learn. 37(2), 183-233 (1999).
-
(1999)
Mach. Learn.
, vol.37
, Issue.2
, pp. 183-233
-
-
Jordan, M.I.1
Ghahramani, Z.2
Jaakkola, T.S.3
Saul, L.K.4
-
11
-
-
71149119166
-
Non-linear matrix factorization with Gaussian processes
-
L. Bottou and M. Littman (Eds.), San Francisco: Morgan Kauffman
-
Lawrence, N. D., Urtasun, R.: Non-linear matrix factorization with Gaussian processes. In: Bottou, L., Littman, M. (eds.) Proceedings of the International Conference in Machine Learning. Morgan Kauffman, San Francisco (2009).
-
(2009)
Proceedings of the International Conference in Machine Learning
-
-
Lawrence, N.D.1
Urtasun, R.2
-
13
-
-
0037252945
-
Amazon.com recommendations: Item-to-item collaborative filtering
-
Linden, G., Smith, B., York, J.: Amazon. com recommendations: Item-to-item collaborative filtering. IEEE Internet Comput. 7(1), 76-80 (2003).
-
(2003)
IEEE Internet Comput.
, vol.7
, Issue.1
, pp. 76-80
-
-
Linden, G.1
Smith, B.2
York, J.3
-
14
-
-
77956495768
-
Mixed membership matrix factorization
-
J. Fürnkranz and T. Joachims (Eds.)
-
Mackey, L., Weiss, D., Jordan, M. I.: Mixed membership matrix factorization. In: Fürnkranz, J., Joachims, T. (eds.) Proceedings of the 27th International Conference on Machine Learning, pp. 711-718 (2010).
-
(2010)
Proceedings of the 27th International Conference on Machine Learning
, pp. 711-718
-
-
Mackey, L.1
Weiss, D.2
Jordan, M.I.3
-
15
-
-
84898970398
-
Modeling user rating profiles for collaborative filtering
-
S. Thrun, L. Saul, B. Schölkopf (Eds.), Cambridge: MIT Press
-
Marlin, B.: Modeling user rating profiles for collaborative filtering. In: Thrun, S., Saul, L., Schölkopf, B. (eds.) Advances in Neural Information Processing Systems, vol. 16. MIT Press, Cambridge (2004).
-
(2004)
Advances in Neural Information Processing Systems
, pp. 16
-
-
Marlin, B.1
-
17
-
-
48349118009
-
The discrete basis problem
-
Miettinen, P., Mielikäinen, T., Gionis, A., Das, G., Mannila, H.: The discrete basis problem. IEEE Trans. Knowl. Data Eng. 10, 1348-1362 (2008).
-
(2008)
IEEE Trans. Knowl. Data Eng.
, vol.10
, pp. 1348-1362
-
-
Miettinen, P.1
Mielikäinen, T.2
Gionis, A.3
Das, G.4
Mannila, H.5
-
24
-
-
85161989354
-
Probabilistic matrix factorization
-
J. Platt, D. Koller, Y. Singer, and S. Roweis (Eds.), Cambridge: MIT Press
-
Salakhutdinov, R., Mnih, A.: Probabilistic matrix factorization. In: Platt, J., Koller, D., Singer, Y., Roweis, S. (eds.) Advances in Neural Information Processing Systems, vol. 20, pp. 1257-1264. MIT Press, Cambridge (2008b).
-
(2008)
Advances in Neural Information Processing Systems
, vol.20
, pp. 1257-1264
-
-
Salakhutdinov, R.1
Mnih, A.2
-
25
-
-
34547983260
-
Restricted Boltzmann machines for collaborative filtering
-
Salakhutdinov, R., Mnih, A., Hinton, G.: Restricted Boltzmann machines for collaborative filtering. In: Proceedings of the International Conference on Machine Learning, vol. 24, pp. 791-798 (2007).
-
(2007)
Proceedings of the International Conference on Machine Learning
, vol.24
, pp. 791-798
-
-
Salakhutdinov, R.1
Mnih, A.2
Hinton, G.3
-
26
-
-
70350623326
-
Mining discrete patterns via binary matrix factorization
-
Shen, B. H., Ji, S., Ye, J.: Mining discrete patterns via binary matrix factorization. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 757-766 (2009).
-
(2009)
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
, pp. 757-766
-
-
Shen, B.H.1
Ji, S.2
Ye, J.3
-
27
-
-
84898932317
-
Maximum-margin matrix factorization
-
Srebro, N., Rennie, J. D. M., Jaakkola, T. S.: Maximum-margin matrix factorization. Adv. Neural Inf. Process. Syst. 17, 1329-1336 (2005).
-
(2005)
Adv. Neural Inf. Process. Syst.
, vol.17
, pp. 1329-1336
-
-
Srebro, N.1
Rennie, J.D.M.2
Jaakkola, T.S.3
-
28
-
-
77950941535
-
-
Stern, D. H., Herbrich, R., Graepel, T.: Matchbox: large scale online Bayesian recommendations. In: WWW, pp. 111-120 (2009).
-
(2009)
Matchbox: Large scale online Bayesian recommendations
, pp. 111-120
-
-
Stern, D.H.1
Herbrich, R.2
Graepel, T.3
-
29
-
-
33750516992
-
On the theory of scales of measurement
-
Stevens, S. S.: On the theory of scales of measurement. Science 103(2684), 677-680 (1946).
-
(1946)
Science
, vol.103
, Issue.2684
, pp. 677-680
-
-
Stevens, S.S.1
-
30
-
-
64149121935
-
Scalable collaborative filtering approaches for large recommender systems
-
Takács, G., Pilászy, I., Németh, B., Tikk, D.: Scalable collaborative filtering approaches for large recommender systems. J. Mach. Learn. Res. 10, 623-656 (2009).
-
(2009)
J. Mach. Learn. Res.
, vol.10
, pp. 623-656
-
-
Takács, G.1
Pilászy, I.2
Németh, B.3
Tikk, D.4
-
32
-
-
71149088913
-
Large-scale collaborative prediction using a nonparametric random effects model
-
L. Bottou and M. Littman (Eds.), San Francisco: Morgan Kauffman
-
Yu, K., Lafferty, J., Zhu, S., Gong, Y.: Large-scale collaborative prediction using a nonparametric random effects model. In: Bottou, L., Littman, M. (eds.) Proceedings of the International Conference in Machine Learning. Morgan Kauffman, San Francisco (2009a).
-
(2009)
Proceedings of the International Conference in Machine Learning
-
-
Yu, K.1
Lafferty, J.2
Zhu, S.3
Gong, Y.4
-
33
-
-
72449152230
-
Fast nonparametric matrix factorization for large-scale collaborative filtering
-
Yu, K., Zhu, S., Lafferty, J., Gong, Y.: Fast nonparametric matrix factorization for large-scale collaborative filtering. In: Proceedings of the 32nd International ACM SIGIR Conference, pp. 211-218 (2009b).
-
(2009)
Proceedings of the 32nd International ACM SIGIR Conference
, pp. 211-218
-
-
Yu, K.1
Zhu, S.2
Lafferty, J.3
Gong, Y.4
-
34
-
-
84859751150
-
Binary matrix factorization for analyzing gene expression data
-
Zhang, Z. Y., Li, T., Ding, C., Ren, X. W., Zhang, X. S.: Binary matrix factorization for analyzing gene expression data. Data Min. Knowl. Discov., 1-25 (2009).
-
(2009)
Data Min. Knowl. Discov
, pp. 1-25
-
-
Zhang, Z.Y.1
Li, T.2
Ding, C.3
Ren, X.W.4
Zhang, X.S.5
-
35
-
-
83855162681
-
Stochastic relational models for large-scale dyadic data using MCMC
-
D. Koller, D. Schuurmans, Y. Bengio, and L. Bottou (Eds.)
-
Zhu, S., Yu, K., Gong, Y.: Stochastic relational models for large-scale dyadic data using MCMC. In: Koller, D., Schuurmans, D., Bengio, Y., Bottou, L. (eds.) Advances in Neural Information Processing Systems, vol. 21, pp. 1993-2000 (2009).
-
(2009)
Advances in Neural Information Processing Systems
, vol.21
, pp. 1993-2000
-
-
Zhu, S.1
Yu, K.2
Gong, Y.3
|