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* [[Mathematician#SIoffe|Sergey Ioffe]] ('''2017'''). ''Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models''. [https://arxiv.org/abs/1702.03275 arXiv:1702.03275]
* [[Ti-Rong Wu]], [[I-Chen Wu]], [[Guan-Wun Chen]], [[Ting-Han Wei]], [[Tung-Yi Lai]], [[Hung-Chun Wu]], [[Li-Cheng Lan]] ('''2017'''). ''Multi-Labelled Value Networks for Computer Go''. [https://arxiv.org/abs/1705.10701 arXiv:1705.10701]
* [[Olivier Bousquet]], [[Sylvain Gelly]], [[Karol Kurach]], [[Marc Schoenauer]], [[Michèle Sebag]], [[Olivier Teytaud]], [[Damien Vincent]] ('''2017'''). ''Toward Optimal Run Racing: Application to Deep Learning Calibration''. [https://arxiv.org/abs/1706.03199 arXiv:1706.03199]
* [[Matej Moravčík]], [[Martin Schmid]], [[Neil Burch]], [[Viliam Lisý]], [[Dustin Morrill]], [[Nolan Bard]], [[Trevor Davis]], [[Kevin Waugh]], [[Michael Johanson]], [[Michael Bowling]] ('''2017'''). ''[http://science.sciencemag.org/content/356/6337/508 DeepStack: Expert-level artificial intelligence in heads-up no-limit poker]''. [https://en.wikipedia.org/wiki/Science_(journal) Science], Vol. 356, No. 6337
* [[Tristan Cazenave]] ('''2017'''). ''Improved Policy Networks for Computer Go''. [[Advances in Computer Games 15]], [http://www.lamsade.dauphine.fr/~cazenave/papers/gofairsbn.pdf pdf]
* [[George Philipp]], [[Mathematician#DawnSong|Dawn Song]], [[Jaime Carbonell]] ('''2017'''). ''The exploding gradient problem demystified - definition, prevalence, impact, origin, tradeoffs, and solutions''. [https://arxiv.org/abs/1712.05577 arXiv:1712.05577]
* [[David Silver]], [[Julian Schrittwieser]], [[Karen Simonyan]], [[Ioannis Antonoglou]], [[Shih-Chieh Huang|Aja Huang]], [[Arthur Guez]], [[Thomas Hubert]], [[Lucas Baker]], [[Matthew Lai]], [[Adrian Bolton]], [[Yutian Chen]], [[Timothy Lillicrap]], [[Fan Hui]], [[Laurent Sifre]], [[George van den Driessche]], [[Thore Graepel]], [[Demis Hassabis]] ('''2017'''). ''[https://www.nature.com/nature/journal/v550/n7676/full/nature24270.html Mastering the game of Go without human knowledge]''. [https://en.wikipedia.org/wiki/Nature_%28journal%29 Nature], Vol. 550, [https://www.gwern.net/docs/rl/2017-silver.pdf pdf] <ref>[https://deepmind.com/blog/alphago-zero-learning-scratch/ AlphaGo Zero: Learning from scratch] by [[Demis Hassabis]] and [[David Silver]], [[DeepMind]], October 18, 2017</ref>
* [[Alice Schoenauer-Sebag]], [[Marc Schoenauer]], [[Michèle Sebag]] ('''2017'''). ''Stochastic Gradient Descent: Going As Fast As Possible But Not Faster''. [https://arxiv.org/abs/1709.01427 arXiv:1709.01427]
* [http://www.peterhenderson.co/ Peter Henderson], [https://scholar.google.ca/citations?user=2_4Rs44AAAAJ&hl=en Riashat Islam], [[Philip Bachman]], [[Joelle Pineau]], [[Doina Precup]], [https://scholar.google.ca/citations?user=gFwEytkAAAAJ&hl=en David Meger] ('''2017'''). ''Deep Reinforcement Learning that Matters''. [https://arxiv.org/abs/1709.06560 arXiv:1709.06560]
* [[David Silver]], [[Thomas Hubert]], [[Julian Schrittwieser]], [[Ioannis Antonoglou]], [[Matthew Lai]], [[Arthur Guez]], [[Marc Lanctot]], [[Laurent Sifre]], [[Dharshan Kumaran]], [[Thore Graepel]], [[Timothy Lillicrap]], [[Karen Simonyan]], [[Demis Hassabis]] ('''2017'''). ''Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm''. [https://arxiv.org/abs/1712.01815 arXiv:1712.01815] » [[AlphaZero]]
