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One problem in the application of reinforcement learning to real-world problems is the curse of dimensionality on the action space.
Favae: Sequence disentanglement using information bottleneck principle
Masanori Yamada, Kim Heecheol, Kosuke Miyoshi, and Hiroshi Yamakawa · 1903
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Reducing the dimensionality of data with neural networks
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Extracting and composing robust features with denoising autoencoders
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Auto-encoding variational bayes
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Human-level control through deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Andrei A Rusu, Joel Veness, Marc G Bellemare, Alex Graves, Martin Riedmiller, Andreas K Fidjeland, Georg Ostrovski, et al · 2015
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Deep reinforcement learning with macro-actions
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Mastering the game of go with deep neural networks and tree search
David Silver, Aja Huang, Chris J Maddison, Arthur Guez, Laurent Sifre, George Van Den Driessche, Julian Schrittwieser, Ioannis Antonoglou, Veda Panneershelvam, Marc Lanctot, et al · 2016
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Strategic attentive writer for learning macro-actions
Alexander Vezhnevets, Volodymyr Mnih, Simon Osindero, Alex Graves, Oriol Vinyals, John Agapiou, et al · 2016
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Learning to repeat: Fine grained action repetition for deep reinforcement learning
Sahil Sharma, Aravind S Lakshminarayanan, and Balaraman Ravindran · 2017
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Mastering the game of go without human knowledge
David Silver, Julian Schrittwieser, Karen Simonyan, Ioannis Antonoglou, Aja Huang, Arthur Guez, Thomas Hubert, Lucas Baker, Matthew Lai, Adrian Bolton, et al · 2017
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Understanding disentangling in β \beta -vae
Christopher P Burgess, Irina Higgins, Arka Pal, Loic Matthey, Nick Watters, Guillaume Desjardins, and Alexander Lerchner · 2018
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beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 2017
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Dynamic action repetition for deep reinforcement learning
Aravind S Lakshminarayanan, Sahil Sharma, and Balaraman Ravindran · 2017
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Tuomas Haarnoja, Aurick Zhou, Sehoon Ha, Jie Tan, George Tucker, and Sergey Levine · 2018
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Time series segmentation through automatic feature learning
Wei-Han Lee, Jorge Ortiz, Bongjun Ko, and Ruby Lee · 2018
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Openai five
OpenAI · 2018
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