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This paper investigates the notion of learning user and item representations in non-Euclidean space.
Distance Metric Learning with Application to Clustering with Side-Information. In Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, NIPS 2002, December 9-14, 2002, Vancouver, British Columbia, Canada] . 505–512
Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, and Stuart J. Russell. 2002 · 2002
Earlier work this paper cites.
Learning a Similarity Metric Discriminatively, with Application to Face Verification. In 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2005), 20-26 June 2005, San Diego, CA, USA . 539–546
Sumit Chopra, Raia Hadsell, and Yann LeCun. 2005 · 2005
Earlier work this paper cites.
Distance Metric Learning for Large Margin Nearest Neighbor Classification. In Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, NIPS 2005, December 5-8, 2005, Vancouver, British Columbia, Canada] . 1473–1480
Kilian Q. Weinberger, John Blitzer, and Lawrence K. Saul. 2005 · 2005
Earlier work this paper cites.
Factorization meets the neighborhood: a multifaceted collaborative filtering model. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining . ACM, 426–434
Yehuda Koren. 2008 · 2008
Earlier work this paper cites.
Probabilistic matrix factorization. In Advances in neural information processing systems . 1257–1264
Andriy Mnih and Ruslan R Salakhutdinov. 2008 · 2008
Earlier work this paper cites.
Matrix factorization techniques for recommender systems
Yehuda Koren, Robert Bell, and Chris Volinsky. 2009 · 2009
Earlier work this paper cites.
BPR: Bayesian Personalized Ranking from Implicit Feedback. In UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, Montreal, QC, Canada, June 18-21, 2009 . 452–461
Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009 · 2009
Earlier work this paper cites.
A Gyrovector Space Approach to Hyperbolic Geometry
Abraham Albert Ungar. 2009 · 2009
Earlier work this paper cites.
Hyperbolic Geometry of Complex Networks
Dmitri V. Krioukov, Fragkiskos Papadopoulos, Maksim Kitsak, Amin Vahdat, and Marián Boguñá. 2010 · 2010
Earlier work this paper cites.
Factorization Machines. In ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010 . 995–1000
Steffen Rendle. 2010 · 2010
Earlier work this paper cites.
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
John C. Duchi, Elad Hazan, and Yoram Singer. 2011 · 2011
Earlier work this paper cites.
Metric Learning with Multiple Kernels. In Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, Granada, Spain. 1170–1178
Jun Wang, Huyen Do, Adam Woznica, and Alexandros Kalousis. 2011 · 2011
Earlier work this paper cites.
Non-linear Metric Learning. In Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012, Lake Tahoe, Nevada, United States. 2582–2590
Dor Kedem, Stephen Tyree, Kilian Q. Weinberger, Fei Sha, and Gert R. G. Lanckriet. 2012 · 2012
Earlier work this paper cites.
Stochastic Gradient Descent on Riemannian Manifolds
Silvere Bonnabel. 2013 · 2013
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
Cited alongside, same era.
Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering. In Proceedings of the 25th International Conference on World Wide Web, WWW 2016, Montreal, Canada, April 11 - 15, 2016 . 507–517
Ruining He and Julian McAuley. 2016a · 2016
Cited alongside, same era.
Fast matrix factorization for online recommendation with implicit feedback. In Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval . ACM, 549–558
Xiangnan He, Hanwang Zhang, Min-Yen Kan, and Tat-Seng Chua. 2016 · 2016
Cited alongside, same era.
A General Recommendation Model for Heterogeneous Networks
Tuan-Anh Nguyen Pham, Xutao Li, Gao Cong, and Zhenjie Zhang. 2016 · 2016
Cited alongside, same era.
Representation Tradeoffs for Hyperbolic Embeddings. In Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018 . 4457–4466
Frederic Sala, Christopher De Sa, Albert Gu, and Christopher Ré. 2018 · 2018
Closest in time.
Latent Relational Metric Learning via Memory-based Attention for Collaborative Ranking. In Proceedings of the 2018 World Wide Web Conference (WWW ’18)
Yi Tay, Luu Anh Tuan, and Siu Cheung Hui. 2018a · 2018
Closest in time.
Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering. In Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, WSDM 2018, Marina Del Rey, CA, USA, February 5-9, 2018 . 583–591
Yi Tay, Luu Anh Tuan, and Siu Cheung Hui. 2018b · 2018
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Gradient descent in hyperbolic space
Benjamin Wilson and Matthia Leimeister. 2018 · 2018
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Benjamin Paul Chamberlain, James R. Clough, and Marc Peter Deisenroth. 2017 · 2017
Cited alongside, same era.
Neural Collaborative Filtering. In Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017 . 173–182
Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. 2017 · 2017
Cited alongside, same era.
Collaborative Metric Learning. In Proceedings of the 26th International Conference on World Wide Web, WWW 2017, Perth, Australia, April 3-7, 2017 . 193–201
Cheng-Kang Hsieh, Longqi Yang, Yin Cui, Tsung-Yi Lin, Serge J. Belongie, and Deborah Estrin. 2017 · 2017
Cited alongside, same era.
Poincaré Embeddings for Learning Hierarchical Representations. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 4-9 December 2017, Long Beach, CA, USA . 6338–6347
Maximilian Nickel and Douwe Kiela. 2017 · 2017
Cited alongside, same era.
Hyperspherical Variational Auto-Encoders. In Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, UAI 2018, Monterey, California, USA, August 6-10, 2018 . 856–865
Tim R. Davidson, Luca Falorsi, Nicola De Cao, Thomas Kipf, and Jakub M. Tomczak. 2018 · 2018
Cited alongside, same era.
Embedding Text in Hyperbolic Spaces. In Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs@NAACL-HLT 2018, New Orleans, Louisiana, USA, June 6, 2018 . 59–69
Bhuwan Dhingra, Christopher J. Shallue, Mohammad Norouzi, Andrew M. Dai, and George E. Dahl. 2018 · 2018
Cited alongside, same era.
Hyperbolic Entailment Cones for Learning Hierarchical Embeddings. In Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018 . 1632–1641
Octavian-Eugen Ganea, Gary Bécigneul, and Thomas Hofmann. 2018a · 2018
Cited alongside, same era.
Hyperbolic Neural Networks. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, 3-8 December 2018, Montréal, Canada. 5350–5360
Octavian-Eugen Ganea, Gary Bécigneul, and Thomas Hofmann. 2018b · 2018
Cited alongside, same era.
NeuRec: On Nonlinear Transformation for Personalized Ranking. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI-18 . International Joint Conferences on Artificial Intelligence Organization, 3669–3675
Shuai Zhang, Lina Yao, Aixin Sun, Sen Wang, Guodong Long, and Manqing Dong. 2018 · 2018
Closest in time.
Riemannian Adaptive Optimization Methods. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019
Gary Bécigneul and Octavian-Eugen Ganea. 2019 · 2019
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Scalable Hyperbolic Recommender Systems
Benjamin Paul Chamberlain, Stephen R. Hardwick, David R. Wardrope, Fabon Dzogang, Fabio Daolio, and Saúl Vargas. 2019 · 2019
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Large-Margin Classification in Hyperbolic Space. In Proceedings of Machine Learning Research (Proceedings of Machine Learning Research) . PMLR, 1832–1840
Hyunghoon Cho, Benjamin DeMeo, Jian Peng, and Bonnie Berger. 2019 · 2019
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Learning Mixed-Curvature Representations in Product Spaces. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019
Albert Gu, Frederic Sala, Beliz Gunel, and Christopher Ré. 2019 · 2019
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Hyperbolic Attention Networks. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019
Çaglar Gülçehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter W. Battaglia, Victor Bapst, David Raposo, Adam Santoro, and Nando de Freitas. 2019 · 2019
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Lorentzian Distance Learning for Hyperbolic Representations. In Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA . 3672–3681
Marc Teva Law, Renjie Liao, Jake Snell, and Richard S. Zemel. 2019 · 2019
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Poincare Glove: Hyperbolic Word Embeddings. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019
Alexandru Tifrea, Gary Bécigneul, and Octavian-Eugen Ganea. 2019 · 2019
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Signed Distance-based Deep Memory Recommender. In The World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019 . 1841–1852
Thanh Tran, Xinyue Liu, Kyumin Lee, and Xiangnan Kong. 2019a · 2019
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Adversarial Mahalanobis Distance-based Attentive Song Recommender for Automatic Playlist Continuation. In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, Paris, France, July 21-25, 2019. 245–254
Thanh Tran, Renee Sweeney, and Kyumin Lee. 2019b · 2019
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