Fetching the paper…
Reading the bibliography…
Log-linear models are arguably the most successful class of graphical models for large-scale applications because of their simplicity and tractability.
The return period of flood flows
Gumbel, E. J · 1941
Earlier work this paper cites.
Statistical theory of extreme values and some practical applications: a series of lectures
Gumbel, Emil Julius and Lieblein, Julius · 1954
Earlier work this paper cites.
Building a large annotated corpus of english: The penn treebank
Marcus, Mitchell P, Marcinkiewicz, Mary Ann, and Santorini, Beatrice · 1993
Earlier work this paper cites.
Graphical models , volume 17
Lauritzen, Steffen L · 1996
Earlier work this paper cites.
Similarity search in high dimensions via hashing
Gionis, Aristides, Indyk, Piotr, Motwani, Rajeev, et al · 1999
Earlier work this paper cites.
A bit of progress in language modeling
Goodman, Joshua T · 2001
Earlier work this paper cites.
Annealed importance sampling
Neal, Radford M · 2001
Earlier work this paper cites.
Similarity estimation techniques from rounding algorithms
Charikar, Moses S · 2002
Earlier work this paper cites.
E2lsh: Exact euclidean locality sensitive hashing
Andoni, Alexandr and Indyk, Piotr · 2004
Cited alongside, same era.
Hierarchical probabilistic neural network language model
Morin, Frederic and Bengio, Yoshua · 2005
Cited alongside, same era.
Imagenet: A large-scale hierarchical image database
Deng, Jia, Dong, Wei, Socher, Richard, Li, Li-Jia, Li, Kai, and Fei-Fei, Li · 2009
Cited alongside, same era.
Probabilistic graphical models: principles and techniques
Koller, Daphne and Friedman, Nir · 2009
Cited alongside, same era.
Similarity search and locality sensitive hashing using ternary content addressable memories
Shinde, Rajendra, Goel, Ashish, Gupta, Pankaj, and Dutta, Debojyoti · 2010
Cited alongside, same era.
One billion word benchmark for measuring progress in statistical language modeling
Dsh: data sensitive hashing for high-dimensional k-nnsearch
Gao, Jinyang, Jagadish, Hosagrahar Visvesvaraya, Lu, Wei, and Ooi, Beng Chin · 2014
Later among the works it cites.
Mining of massive datasets
Leskovec, Jure, Rajaraman, Anand, and Ullman, Jeffrey David · 2014
Later among the works it cites.
Learning longer memory in recurrent neural networks
Mikolov, Tomas, Joulin, Armand, Chopra, Sumit, Mathieu, Michael, and Ranzato, Marc’Aurelio · 2014
Later among the works it cites.
Asymmetric lsh (alsh) for sublinear time maximum inner product search (mips)
Shrivastava, Anshumali and Li, Ping · 2014
Later among the works it cites.
Query-aware locality-sensitive hashing for approximate nearest neighbor search
Huang, Qiang, Feng, Jianlin, Zhang, Yikai, Fang, Qiong, and Ng, Wilfred · 2015
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Chelba, Ciprian, Mikolov, Tomas, Schuster, Mike, Ge, Qi, Brants, Thorsten, Koehn, Phillipp, and Robinson, Tony · 2013
Cited alongside, same era.
Distributed representations of words and phrases and their compositionality
Mikolov, Tomas, Sutskever, Ilya, Chen, Kai, Corrado, Greg S, and Dean, Jeff · 2013
Cited alongside, same era.
Improved asymmetric locality sensitive hashing (alsh) for maximum inner product search (mips)
Shrivastava, Anshumali and Li, Ping
Cited in the paper.
Asymmetric minwise hashing for indexing binary inner products and set containment
Shrivastava, Anshumali and Li, Ping
Cited in the paper.
Liu, Qiang, Peng, Jian, Ihler, Alexander, and Fisher III, John · 2015
Later among the works it cites.
Learning and inference via maximum inner product search
Mussmann, Stephen and Ermon, Stefano · 2016
Later among the works it cites.