Deep Sequential Modeling for Recommendation
暂无分享,去创建一个
[1] George Karypis,et al. FISM: factored item similarity models for top-N recommender systems , 2013, KDD.
[2] Ruslan Salakhutdinov,et al. Probabilistic Matrix Factorization , 2007, NIPS.
[3] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[4] Lars Schmidt-Thieme,et al. Factorizing personalized Markov chains for next-basket recommendation , 2010, WWW '10.
[5] Hugues Bersini,et al. Long and Short-Term Recommendations with Recurrent Neural Networks , 2017, UMAP.
[6] Lars Schmidt-Thieme,et al. BPR: Bayesian Personalized Ranking from Implicit Feedback , 2009, UAI.
[7] Nicola Barbieri,et al. Probabilistic topic models for sequence data , 2013, Machine Learning.
[8] Daan Wierstra,et al. Stochastic Backpropagation and Approximate Inference in Deep Generative Models , 2014, ICML.
[9] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[10] Ke Wang,et al. Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding , 2018, WSDM.
[11] Vikram Pudi,et al. Sequential Variational Autoencoders for Collaborative Filtering , 2018, WSDM.
[12] Julian J. McAuley,et al. Translation-based Recommendation , 2017, RecSys.
[13] James She,et al. Collaborative Variational Autoencoder for Recommender Systems , 2017, KDD.
[14] Thomas Hofmann,et al. Latent semantic models for collaborative filtering , 2004, TOIS.
[15] Chong Wang,et al. Collaborative topic modeling for recommending scientific articles , 2011, KDD.
[16] Alexandros Karatzoglou,et al. Session-based Recommendations with Recurrent Neural Networks , 2015, ICLR.
[17] Matthew D. Hoffman,et al. Variational Autoencoders for Collaborative Filtering , 2018, WWW.
[18] Alex Beutel,et al. Recurrent Recommender Networks , 2017, WSDM.