Fetching the paper…
Reading the bibliography…
In this work, we attempt to ameliorate the impact of data sparsity in the context of session-based recommendation.
Learning internal representations by error propagation
D.E. Rumelhart, G.E. Hinton, and R.J. Williams. 1986 · 1986
Earlier work this paper cites.
Long short-term memory
S. Hochreiter and J. Schmidhuber. 1997 · 1997
Earlier work this paper cites.
An introduction to variational methods for graphical models
M.I. Jordan, Z. Ghahramani, T.S. Jaakkola, and L.K. Saul. 1998 · 1998
Earlier work this paper cites.
On the momentum term in gradient descent learning algorithms
N. Qian. 1999 · 1999
Earlier work this paper cites.
Recommender systems in e-commerce. In Proc. 1st ACM Conference on Electronic Commerce, EC ’99
B. Schafer, J. Konstan, and J. Riedl. 1999 · 1999
Earlier work this paper cites.
Latent semantic models for collaborative filtering
T. Hofmann. 2004 · 2004
Earlier work this paper cites.
Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
G. Adomavicius and A. Tuzhilin. 2005 · 2005
Earlier work this paper cites.
An MDP-Based Recommender System
Guy Shani, David Heckerman, and Ronen I. Brafman. 2005 · 2005
Earlier work this paper cites.
Collaborative prediction using ensembles of maximum margin matrix factorizations. In Proc. ICML’06
D. DeCoste. 2006 · 2006
Earlier work this paper cites.
Probabilistic Matrix Factorization. In Proc. NIPS’07
Ruslan Salakhutdinov and Andriy Mnih. 2007 · 2007
Earlier work this paper cites.
Restricted Boltzmann machines for collaborative filtering. In Proc. ICML’07
R. Salakhutdinov, A. Mnih, and G. Hinton. 2007 · 2007
Earlier work this paper cites.
Factorization meets the neighborhood: a multifaceted collaborative filtering model. In Proc.14th ACM SIGKDD
Y. Koren. 2008 · 2008
Cited alongside, same era.
Collaborative filtering for Orkut communities: discovery of user latent behavior. In Proc. WWW’09
Wen Y. Chen, Jon C. Chu, Junyi Luan, Hongjie Bai, Yi Wang, and Edward Y. Chang. 2009 · 2009
Cited alongside, same era.
BPR: Bayesian personalized ranking from implicit feedback. In Proc. UAI’09
S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme. 2009 · 2009
Cited alongside, same era.
Adaptive subgradient methods for online learning and stochastic optimization
John Duchi, Elad Hazan, and Yoram Singer. 2010 · 2010
Cited alongside, same era.
Understanding the difficulty of training deep feedforward neural networks. In Proc. AISTATS
X. Glorot and Y. Bengio. 2010 · 2010
Cited alongside, same era.
Advances in optimizing recurrent networks. In Proc. ICASSP
Y. Bengio, N. Boulanger-Lewandowski, and R. Pascanu. 2013 · 2013
Later among the works it cites.
Nonparametric Bayesian Multitask Collaborative Filtering. In Proc. CIKM’13
Sotirios P. Chatzis. 2013 · 2013
Later among the works it cites.
On the properties of neural machine translation: Encoder-decoder approaches. In Proc. Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation (SSST-8)
Kyunghyun Cho, Bart van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio. 2014 · 2014
Later among the works it cites.
Auto-Encoding Variational Bayes. In Proc. ICLR’14
D. Kingma and M. Welling. 2014 · 2014
Later among the works it cites.
Semi-Supervised Learning with Deep Generative Models. In Proc. NIPS’14
D. P. Kingma, D. J. Rezende, S. Mohamed, and M. Welling. 2014 · 2014
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Bayesian Matrix Factorization with Side Information and Dirichlet Process Mixtures. In Proc. AAAI-10
Ian Porteous, Arthur Asuncion, and Max Welling. 2010 · 2010
Cited alongside, same era.
Bayesian Latent Variable Models for Collaborative Item Rating Prediction. In Proc. CIKM ’11
Morgan Harvey, Mark J. Carman, Ian Ruthven, and Fabio Crestani. 2011 · 2011
Cited alongside, same era.
Theoretical Analysis of Bayesian Matrix Factorization
Shinichi Nakajima and Masashi Sugiyama. 2011 · 2011
Cited alongside, same era.
Bayesian Probabilistic Matrix Factorization using Markov Chain Monte Carlo. In Proc. ICML’11
Ruslan Salakhutdinov and Andriy Mnih. 2011 · 2011
Cited alongside, same era.
Theano: new features and speed improvements
Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, and Yoshua Bengio. 2012 · 2012
Cited alongside, same era.
A Coupled Indian Buffet Process Model for Collaborative Filtering. In Journal of Machine Learning Research: Workshop and Conference Proceedings
Sotirios P. Chatzis. 2012 · 2012
Cited alongside, same era.
Sequential click prediction for sponsored search with recurrent neural networks. In Proc. AAAI-14
Y. Zhang, H. Dai, C. Xu, J. Feng, T. Wang, J. Bian, B. Wang, and T.-Y. Liu. 2014 · 2014
Later among the works it cites.
RecSys Challenge 2015 and the YOOCHOOSE Dataset. In Proceedings of the 9th ACM Conference on Recommender Systems
David Ben-Shimon, Alexander Tsikinovsky, Michael Friedmann, Bracha Shapira, Lior Rokach, and Johannes Hoerle. 2015 · 2015
Later among the works it cites.
Deep learning
Y. LeCun, Y. Bengio, and G. Hinton. 2015 · 2015
Later among the works it cites.
Collaborative deep learning for recommender systems. In Proc. 21st ACM SIGKDD
H. Wang, N. Wang, and D.-Y. Yeung. 2015 · 2015
Later among the works it cites.
Session-based recommendations with recurrent neural networks. In Proc. ICLR’16
B. Hidasi, A. Karatzoglou, L. Baltrunas, and D. Tikk. 2016 · 2016
Later among the works it cites.
Improved Recurrent Neural Networks for Session-based Recommendations. In Proc. DLRS ’16
Yong Kiam Tan, Xinxing Xu, and Yong Liu. 2016 · 2016
Later among the works it cites.