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Efficient Maximum Inner Product Search (MIPS) is an important task that has a wide applicability in recommendation systems and classification with a large number of classes.
A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Janvin · 2003
Earlier work this paper cites.
Locality-sensitive hashing scheme based on p-stable distributions
Mayur Datar, Nicole Immorlica, Piotr Indyk, and Vahab S. Mirrokni · 2004
Earlier work this paper cites.
Hierarchical probabilistic neural network language model
Frederic Morin and Yoshua Bengio · 2005
Earlier work this paper cites.
Efficient online spherical k-means clustering
Shi Zhong · 2005
Earlier work this paper cites.
A scalable hierarchical distributed language model
Andriy Mnih and Geoffrey Hinton · 2009
Earlier work this paper cites.
Theano: a CPU and GPU math expression compiler
James Bergstra, Olivier Breuleux, Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, Guillaume Desjardins, Joseph Turian, David Warde-Farley, and Yoshua Bengio · 2010
Earlier work this paper cites.
Performance of recommender algorithms on top-n recommendation tasks
Paolo Cremonesi, Yehuda Koren, and Roberto Turrin · 2010
Cited alongside, same era.
Efficient retrieval of recommendations in a matrix factorization framework
Noam Koenigstein, Parikshit Ram, and Yuval Shavitt · 2012
Cited alongside, same era.
Maximum inner-product search using cone trees
Parikshit Ram and Alexander G. Gray · 2012
Cited alongside, same era.
Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Cited alongside, same era.
Speeding up the xbox recommender system using a euclidean transformation for inner-product spaces
Yoram Bachrach, Yehuda Finkelstein, Ran Gilad-Bachrach, Liran Katzir, Noam Koenigstein, Nir Nice, and Ulrich Paquet · 2014
Cited alongside, same era.
Asymmetric LSH (ALSH) for sublinear time maximum inner product search (MIPS)
Anshumali Shrivastava and Ping Li · 2014
Later among the works it cites.
Deep networks with large output spaces
Sudheendra Vijayanarasimhan, Jon Shlens, Rajat Monga, and Jay Yagnik · 2014
Later among the works it cites.
Quantization based fast inner product search
Ruiqi Guo, Sanjiv Kumar, Krzysztof Choromanski, and David Simcha · 2015
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On symmetric and asymmetric lshs for inner product search
Behnam Neyshabur and Nathan Srebro · 2015
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Improved asymmetric locality sensitive hashing (alsh) for maximum inner product search (mips)
Anshumali Shrivastava and Ping Li · 2015
Closest in time.
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