-
2
-
-
85008044987
-
Matrix factorization techniques for recommender systems
-
Yehuda Koren, Robert M. Bell, and Chris Volinsky. Matrix factorization techniques for recommender systems. IEEE Computer, 42(8):30-37, 2009.
-
(2009)
IEEE Computer
, vol.42
, Issue.8
, pp. 30-37
-
-
Koren, Y.1
Bell, R.M.2
Volinsky, C.3
-
3
-
-
84889586257
-
Nonparametric Bayesian multitask collaborative filtering
-
Sotirios Chatzis. Nonparametric bayesian multitask collaborative filtering. In CIKM, pages 2149-2158, 2013.
-
(2013)
CIKM
, pp. 2149-2158
-
-
Chatzis, S.1
-
4
-
-
48349135120
-
Probabilistic matrix factorization
-
Ruslan Salakhutdinov and Andriy Mnih. Probabilistic matrix factorization. In NIPS, 2007.
-
(2007)
NIPS
-
-
Salakhutdinov, R.1
Mnih, A.2
-
5
-
-
79952399179
-
Recommender systems with social regularization
-
Hao Ma, Dengyong Zhou, Chao Liu, Michael R. Lyu, and Irwin King. Recommender systems with social regularization. In WSDM, pages 287-296, 2011.
-
(2011)
WSDM
, pp. 287-296
-
-
Ma, H.1
Zhou, D.2
Liu, C.3
Lyu, M.R.4
King, I.5
-
6
-
-
65449121541
-
Relational learning via collective matrix factorization
-
Ajit Paul Singh and Geoffrey J. Gordon. Relational learning via collective matrix factorization. In KDD, pages 650-658, 2008.
-
(2008)
KDD
, pp. 650-658
-
-
Singh, A.P.1
Gordon, G.J.2
-
7
-
-
84977857699
-
A Bayesian matrix factorization model for relational data
-
Ajit Paul Singh and Geoffrey J. Gordon. A bayesian matrix factorization model for relational data. CoRR, abs/1203.3517, 2012.
-
(2012)
CoRR, Abs/1203.3517
-
-
Singh, A.P.1
Gordon, G.J.2
-
8
-
-
33746600649
-
Reducing the dimensionality of data with neural networks
-
Geoffrey E Hinton and Ruslan R Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006.
-
(2006)
Science
, vol.313
, Issue.5786
, pp. 504-507
-
-
Hinton, G.E.1
Salakhutdinov, R.R.2
-
9
-
-
33745805403
-
A fast learning algorithm for deep belief nets
-
Geoffrey Hinton, Simon Osindero, and Yee-Whye Teh. A fast learning algorithm for deep belief nets. Neural computation, 18(7):1527-1554, 2006.
-
(2006)
Neural Computation
, vol.18
, Issue.7
, pp. 1527-1554
-
-
Hinton, G.1
Osindero, S.2
Teh, Y.-W.3
-
10
-
-
34547983260
-
Restricted boltzmann machines for collaborative filtering
-
Ruslan Salakhutdinov, Andriy Mnih, and Geoffrey E. Hinton. Restricted boltzmann machines for collaborative filtering. In ICML, pages 791-798, 2007.
-
(2007)
ICML
, pp. 791-798
-
-
Salakhutdinov, R.1
Mnih, A.2
Hinton, G.E.3
-
11
-
-
84897544713
-
A non-iid framework for collaborative filtering with restricted boltzmann machines
-
Kostadin Georgiev and Preslav Nakov. A non-iid framework for collaborative filtering with restricted boltzmann machines. In ICML, pages 1148-1156, 2013.
-
(2013)
ICML
, pp. 1148-1156
-
-
Georgiev, K.1
Nakov, P.2
-
12
-
-
84913528232
-
Improving content-based and hybrid music recommendation using deep learning
-
Xinxi Wang and Ye Wang. Improving content-based and hybrid music recommendation using deep learning. In ACM MM, pages 627-636, 2014.
-
(2014)
ACM MM
, pp. 627-636
-
-
Wang, X.1
Wang, Y.2
-
13
-
-
84898973716
-
Deep content-based music recommendation
-
Aäron Van Den Oord, Sander Dieleman, and Benjamin Schrauwen. Deep content-based music recommendation. In NIPS, pages 2643-2651, 2013.
-
(2013)
NIPS
, pp. 2643-2651
-
-
Van Den Oord, A.1
Dieleman, S.2
Schrauwen, B.3
-
14
-
-
80053145987
-
Ordinal boltzmann machines for collaborative filtering
-
Tran The Truyen, Dinh Q. Phung, and Svetha Venkatesh. Ordinal boltzmann machines for collaborative filtering. In UAI, pages 548-556, 2009.
-
(2009)
UAI
, pp. 548-556
-
-
Truyen, T.T.1
Phung, D.Q.2
Venkatesh, S.3
-
16
-
-
84867129067
-
Marginalized denoising autoencoders for domain adaptation
-
Minmin Chen, Zhixiang Eddie Xu, Kilian Q. Weinberger, and Fei Sha. Marginalized denoising autoencoders for domain adaptation. In ICML, 2012.
-
(2012)
ICML
-
-
Chen, M.1
Xu, Z.E.2
Weinberger, K.Q.3
Sha, F.4
-
17
-
-
77955202099
-
-
Springer
-
Francesco Ricci, Lior Rokach, Bracha Shapira, and Paul B Kantor. Recommender systems handbook, volume 1. Springer, 2011.
-
(2011)
Recommender Systems Handbook
, vol.1
-
-
Ricci, F.1
Rokach, L.2
Shapira, B.3
Kantor, P.B.4
-
20
-
-
84898964201
-
Algorithms for non-negative matrix factorization
-
Daniel D Lee and H Sebastian Seung. Algorithms for non-negative matrix factorization. In NIPS, pages 556-562, 2001.
-
(2001)
NIPS
, pp. 556-562
-
-
Lee, D.D.1
Sebastian Seung, H.2
-
21
-
-
56449131205
-
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
-
Ruslan Salakhutdinov and Andriy Mnih. Bayesian probabilistic matrix factorization using markov chain monte carlo. In ICML, pages 880-887, 2008.
-
(2008)
ICML
, pp. 880-887
-
-
Salakhutdinov, R.1
Mnih, A.2
-
22
-
-
84897476679
-
Fast max-margin matrix factorization with data augmentation
-
Minjie Xu, Jun Zhu, and Bo Zhang. Fast max-margin matrix factorization with data augmentation. ICML, 2013.
-
(2013)
ICML
-
-
Xu, M.1
Zhu, J.2
Zhang, B.3
-
23
-
-
84896061534
-
SCMF: Sparse covariance matrix factorization for collaborative filtering
-
Jianping Shi, Naiyan Wang, Yang Xia, Dit-Yan Yeung, Irwin King, and Jiaya Jia. SCMF: sparse covariance matrix factorization for collaborative filtering. In IJCAI, 2013.
-
(2013)
IJCAI
-
-
Shi, J.1
Wang, N.2
Xia, Y.3
Yeung, D.-Y.4
King, I.5
Jia, J.6
-
24
-
-
80052416079
-
Incorporating side information in probabilistic matrix factorization with Gaussian processes
-
Ryan Prescott Adams, George E. Dahl, and Iain Murray. Incorporating side information in probabilistic matrix factorization with gaussian processes. In UAI, pages 1-9, 2010.
-
(2010)
UAI
, pp. 1-9
-
-
Adams, R.P.1
Dahl, G.E.2
Murray, I.3
-
25
-
-
84930194482
-
Leveraging social connections to improve personalized ranking for collaborative filtering
-
Tong Zhao, Julian J. McAuley, and Irwin King. Leveraging social connections to improve personalized ranking for collaborative filtering. In CIKM, pages 261-270, 2014.
-
(2014)
CIKM
, pp. 261-270
-
-
Zhao, T.1
McAuley, J.J.2
King, I.3
-
26
-
-
85071783077
-
Bayesian matrix factorization with side information and dirichlet process mixtures
-
Ian Porteous, Arthur U. Asuncion, and Max Welling. Bayesian matrix factorization with side information and dirichlet process mixtures. In AAAI, 2010.
-
(2010)
AAAI
-
-
Porteous, I.1
Asuncion, A.U.2
Welling, M.3
-
27
-
-
84955480178
-
Scalable variational Bayesian matrix factorization with side information
-
Yong-Deok Kim and Seungjin Choi. Scalable variational bayesian matrix factorization with side information. In AISTATS, pages 493-502, 2014.
-
(2014)
AISTATS
, pp. 493-502
-
-
Kim, Y.-D.1
Choi, S.2
-
28
-
-
84896061714
-
Hierarchical Bayesian matrix factorization with side information
-
Sunho Park, Yong-Deok Kim, and Seungjin Choi. Hierarchical bayesian matrix factorization with side information. In IJCAI, 2013.
-
(2013)
IJCAI
-
-
Park, S.1
Kim, Y.-D.2
Choi, S.3
-
29
-
-
84891773848
-
Personalized recommendation via cross-domain triadic factorization
-
Liang Hu, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu, and Can Zhu. Personalized recommendation via cross-domain triadic factorization. In WWW, pages 595-606, 2013.
-
(2013)
WWW
, pp. 595-606
-
-
Hu, L.1
Cao, J.2
Xu, G.3
Cao, L.4
Gu, Z.5
Zhu, C.6
-
30
-
-
80052679175
-
Response prediction using collaborative filtering with hierarchies and side-information
-
Aditya Krishna Menon, Krishna Prasad Chitrapura, Sachin Garg, Deepak Agarwal, and Nagaraj Kota. Response prediction using collaborative filtering with hierarchies and side-information. In KDD, pages 141-149, 2011.
-
(2011)
KDD
, pp. 141-149
-
-
Menon, A.K.1
Chitrapura, K.P.2
Garg, S.3
Agarwal, D.4
Kota, N.5
-
31
-
-
84953707906
-
Predicting user behavior in display advertising via dynamic collective matrix factorization
-
Sheng Li, Jaya Kawale, and Yun Fu. Predicting user behavior in display advertising via dynamic collective matrix factorization. In SIGIR, 2015.
-
(2015)
SIGIR
-
-
Li, S.1
Kawale, J.2
Fu, Y.3
-
32
-
-
84908151646
-
Deep modeling of group preferences for group-based recommendation
-
Liang Hu, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu, and Wei Cao. Deep modeling of group preferences for group-based recommendation. In AAAI, pages 1861-1867, 2014.
-
(2014)
AAAI
, pp. 1861-1867
-
-
Hu, L.1
Cao, J.2
Xu, G.3
Cao, L.4
Gu, Z.5
Cao, W.6
-
33
-
-
84910016320
-
Autoencoder-based collaborative filtering
-
Yuanxin Ouyang, Wenqi Liu, Wenge Rong, and Zhang Xiong. Autoencoder-based collaborative filtering. In ICONIP, pages 284-291, 2014.
-
(2014)
ICONIP
, pp. 284-291
-
-
Ouyang, Y.1
Liu, W.2
Rong, W.3
Xiong, Z.4
-
34
-
-
56449131205
-
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo
-
ACM
-
Ruslan Salakhutdinov and Andriy Mnih. Bayesian probabilistic matrix factorization using markov chain monte carlo. In ICML, pages 880-887. ACM, 2008.
-
(2008)
ICML
, pp. 880-887
-
-
Salakhutdinov, R.1
Mnih, A.2
-
35
-
-
67049164166
-
Collaborative filtering for implicit feedback datasets
-
Yifan Hu, Yehuda Koren, and Chris Volinsky. Collaborative filtering for implicit feedback datasets. In ICDM, pages 263-272, 2008.
-
(2008)
ICDM
, pp. 263-272
-
-
Hu, Y.1
Koren, Y.2
Volinsky, C.3
-
36
-
-
70450177775
-
Learning invariant features through topographic filter maps
-
IEEE
-
Koray Kavukcuoglu, MarcâAZAurelio Ranzato, Rob Fergus, and Yann Le-Cun. Learning invariant features through topographic filter maps. In CVPR, pages 1605-1612. IEEE, 2009.
-
(2009)
CVPR
, pp. 1605-1612
-
-
Kavukcuoglu, K.1
Ranzato, M.A.2
Fergus, R.3
Yann, L.-C.4
-
37
-
-
84863380535
-
Unsupervised feature learning for audio classification using convolutional deep belief networks
-
Honglak Lee, Peter Pham, Yan Largman, and Andrew Y Ng. Unsupervised feature learning for audio classification using convolutional deep belief networks. In NIPS, pages 1096-1104, 2009.
-
(2009)
NIPS
, pp. 1096-1104
-
-
Lee, H.1
Pham, P.2
Largman, Y.3
Ng, A.Y.4
-
38
-
-
56449089103
-
Extracting and composing robust features with denoising autoencoders
-
ACM
-
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, and Pierre-Antoine Manzagol. Extracting and composing robust features with denoising autoencoders. In ICML, pages 1096-1103. ACM, 2008.
-
(2008)
ICML
, pp. 1096-1103
-
-
Vincent, P.1
Larochelle, H.2
Bengio, Y.3
Manzagol, P.-A.4
-
39
-
-
84919825814
-
Marginalized denoising auto-encoders for nonlinear representations
-
Minmin Chen, Kilian Q. Weinberger, Fei Sha, and Yoshua Bengio. Marginalized denoising auto-encoders for nonlinear representations. In ICML, pages 1476-1484, 2014.
-
(2014)
ICML
, pp. 1476-1484
-
-
Chen, M.1
Weinberger, K.Q.2
Sha, F.3
Bengio, Y.4
-
40
-
-
84937605005
-
Distributed stochastic ADMM for matrix factorization
-
Zhi-Qin Yu, Xing-Jian Shi, Ling Yan, and Wu-Jun Li. Distributed stochastic ADMM for matrix factorization. In CIKM, pages 1259-1268, 2014.
-
(2014)
CIKM
, pp. 1259-1268
-
-
Yu, Z.-Q.1
Shi, X.-J.2
Yan, L.3
Li, W.-J.4
-
41
-
-
65449121157
-
Factorization meets the neighborhood: A multifaceted collaborative filtering model
-
Yehuda Koren. Factorization meets the neighborhood: a multifaceted collaborative filtering model. In KDD, pages 426-434, 2008.
-
(2008)
KDD
, pp. 426-434
-
-
Koren, Y.1
-
42
-
-
84883103691
-
An experimental study on implicit social recommendation
-
Hao Ma. An experimental study on implicit social recommendation. In SIGIR, pages 73-82, 2013.
-
(2013)
SIGIR
, pp. 73-82
-
-
Ma, H.1
-
43
-
-
84921839680
-
Coupled item-based matrix factorization
-
Fangfang Li, Guandong Xu, and Longbing Cao. Coupled item-based matrix factorization. In WISE, pages 1-14, 2014.
-
(2014)
WISE
, pp. 1-14
-
-
Li, F.1
Xu, G.2
Cao, L.3
-
44
-
-
84906852218
-
Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising
-
Amr Ahmed, Abhimanyu Das, and Alexander J. Smola. Scalable hierarchical multitask learning algorithms for conversion optimization in display advertising. In WSDM, pages 153-162, 2014.
-
(2014)
WSDM
, pp. 153-162
-
-
Ahmed, A.1
Das, A.2
Smola, A.J.3
|