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Quantum machine learning has the potential for broad industrial applications, and the development of quantum algorithms for improving the performance of neural networks is of particular interest given the central role they play in machine learning today.
Simulating physics with computers
Richard P Feynman · 1982
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Learning representations by back-propagating errors
David E Rumelhart, Geoffrey E Hinton, and Ronald J Williams · 1986
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Quantum amplitude amplification and estimation
Gilles Brassard, Peter Hoyer, Michele Mosca, and Alain Tapp · 2002
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Do we have brain to spare?
David A Drachman · 2005
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Quantum random access memory
Vittorio Giovannetti, Seth Lloyd, and Lorenzo Maccone · 2008
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio · 2010
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Quantum algorithms for supervised and unsupervised machine learning
Seth Lloyd, Masoud Mohseni, and Patrick Rebentrost · 2013
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Low-rank matrix factorization for deep neural network training with high-dimensional output targets
Tara N Sainath, Brian Kingsbury, Vikas Sindhwani, Ebru Arisoy, and Bhuvana Ramabhadran · 2013
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Quantum algorithms for linear algebra and machine learning
Anupam Prakash · 2014
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Quantum support vector machine for big data classification
Patrick Rebentrost, Masoud Mohseni, and Seth Lloyd · 2014
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Exploiting linear structure within convolutional networks for efficient evaluation
Emily L Denton, Wojciech Zaremba, Joan Bruna, Yann LeCun, and Rob Fergus · 2014
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An introduction to quantum machine learning
Maria Schuld, Ilya Sinayskiy, and Francesco Petruccione · 2015
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Quantum algorithms for nearest-neighbor methods for supervised and unsupervised learning
Nathan Wiebe, Ashish Kapoor, and Krysta M Svore · 2015
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Fast quantum algorithms for least squares regression and statistic leverage scores
Yang Liu and Shengyu Zhang · 2015
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Neural networks and deep learning
Michael Nielsen · 2015
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Convolutional neural networks with low-rank regularization
Cheng Tai, Tong Xiao, Yi Zhang, Xiaogang Wang, and Weinan E · 2015
Cited alongside, same era.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Cited alongside, same era.
Prediction by linear regression on a quantum computer
Maria Schuld, Ilya Sinayskiy, and Francesco Petruccione · 2016
Cited alongside, same era.
Quantum deep learning
Nathan Wiebe, Ashish Kapoor, and Krysta M Svore · 2016
Cited alongside, same era.
On compressing deep models by low rank and sparse decomposition
Xiyu Yu, Tongliang Liu, Xinchao Wang, and Dacheng Tao · 2017
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Quantum linear system algorithm for dense matrices
Leonard Wossnig, Zhikuan Zhao, and Anupam Prakash · 2018
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A quantum-inspired classical algorithm for recommendation systems
Ewin Tang · 2018
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Quantum-inspired classical algorithms for principal component analysis and supervised clustering
Ewin Tang · 2018
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Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension
András Gilyén, Seth Lloyd, and Ewin Tang · 2018
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Ian Goodfellow, Yoshua Bengio, Aaron Courville, and Yoshua Bengio · 2016
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Quantum neuron: an elementary building block for machine learning on quantum computers
Yudong Cao, Gian Giacomo Guerreschi, and Alán Aspuru-Guzik · 2017
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Quantum machine learning
Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd · 2017
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Quantum recommendation systems
Iordanis Kerenidis and Anupam Prakash · 2017
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Quantum gradient descent for linear systems and least squares
Iordanis Kerenidis and Anupam Prakash · 2017
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Quantum generalisation of feedforward neural networks
Kwok Ho Wan, Oscar Dahlsten, Hlér Kristjánsson, Robert Gardner, and MS Kim · 2017
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Machine learning & artificial intelligence in the quantum domain: a review of recent progress
Vedran Dunjko and Hans J Briegel · 2018
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Quantum classification of the mnist dataset via slow feature analysis
Iordanis Kerenidis and Alessandro Luongo · 2018
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Classification with quantum neural networks on near term processors
Edward Farhi and Hartmut Neven · 2018
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Quantum advantage in training binary neural networks
Yidong Liao, Oscar Dahlsten, Daniel Ebler, and Feiyang Liu · 2018
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Quantum hopfield neural network
Patrick Rebentrost, Thomas R Bromley, Christian Weedbrook, and Seth Lloyd · 2018
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q-means: q-means: A quantum algorithm for unsupervised machine learning
Iordanis Kerenidis, Jonas Landman, Alessandro Luongo, and Anupam Prakash · 2018
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Quantum-inspired algorithms in practice
Juan Miguel Arrazola, Alain Delgado, Bhaskar Roy Bardhan, and Seth Lloyd · 2019
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Quantum machine learning in feature hilbert spaces
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Generative training of quantum boltzmann machines with hidden units
Nathan Wiebe and Leonard Wossnig · 2019
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