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Many machine learning tasks require sampling a subset of items from a collection based on a parameterized distribution.
The relationship between luce’s choice axiom, thurstone’s theory of comparative judgment, and the double exponential distribution
John I. Yellott · 1977
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Random sampling with a reservoir
Jeffrey S. Vitter · 1985
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Simple statistical gradient-following algorithms for connectionist reinforcement learning
Ronald J. Williams · 1992
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Weighted random sampling with a reservoir
Pavlos S. Efraimidis and Paul G. Spirakis · 2006
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Visualizing gene interaction graphs with local multidimensional scaling
Jarkko Venna and Samuel Kaski · 2006
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Data for matlab hackers, 2009
Sam Roweis · 2009
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Learning a parametric embedding by preserving local structure
Laurens van der Maaten · 2009
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MNIST handwritten digit database
Yann LeCun and Corinna Cortes · 2010
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Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts · 2011
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Auto-encoding variational bayes, 2013
Diederik P Kingma and Max Welling · 2013
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Convolutional neural networks for sentence classification
Yoon Kim · 2014
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Semi-supervised learning with deep generative models
Durk P Kingma, Shakir Mohamed, Danilo Jimenez Rezende, and Max Welling · 2014
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Gumbel-max trick and weighted reservoir sampling, 2014
Tim Vieira · 2014
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A hierarchical neural autoencoder for paragraphs and documents
Jiwei Li, Minh-Thang Luong, and Dan Jurafsky · 2015
Exact sampling with integer linear programs and random perturbations
Carolyn Kim, Ashish Sabharwal, and Stefano Ermon · 2016
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GANS for sequences of discrete elements with the gumbel-softmax distribution
Matt J. Kusner and José Miguel Hernández-Lobato · 2016
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The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison, Andriy Mnih, and Yee Whye Teh · 2017
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Learning to explain: An information-theoretic perspective on model interpretation
Jianbo Chen, Le Song, Martin Wainwright, and Michael Jordan · 2018
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Neural nearest neighbors networks
Tobias Plötz and Stefan Roth · 2018
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Stochastic optimization of sorting networks via continuous relaxations
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Show, attend and tell: Neural image caption generation with visual attention
Kelvin Xu, Jimmy Lei Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhutdinov, Richard S. Zemel, and Yoshua Bengio · 2015
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2016
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Aditya Grover, Eric Wang, Aaron Zweig, and Stefano Ermon · 2019
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Stochastic beams and where to find them: The Gumbel-top-k trick for sampling sequences without replacement
Wouter Kool, Herke Van Hoof, and Max Welling · 2019
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