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* [https://github.com/andravin Andrew Lavin], [https://github.com/scott-gray Scott Gray] ('''2015'''). ''Fast Algorithms for Convolutional Neural Networks''. [https://arxiv.org/abs/1509.09308 arXiv:1509.09308] <ref>[http://www.talkchess.com/forum/viewtopic.php?t=66025&start=3 Re: To TPU or not to TPU...] by [[Rémi Coulom]], [[CCC]], December 16, 2017</ref>
* [[Volodymyr Mnih]], [[Koray Kavukcuoglu]], [[David Silver]], [[Andrei A. Rusu]], [[Joel Veness]], [[Marc G. Bellemare]], [[Alex Graves]], [[Martin Riedmiller]], [[Andreas K. Fidjeland]], [[Georg Ostrovski]], [[Stig Petersen]], [[Charles Beattie]], [[Amir Sadik]], [[Ioannis Antonoglou]], [[Helen King]], [[Dharshan Kumaran]], [[Daan Wierstra]], [[Shane Legg]], [[Demis Hassabis]] ('''2015'''). ''[http://www.nature.com/nature/journal/v518/n7540/abs/nature14236.html Human-level control through deep reinforcement learning]''. [https://en.wikipedia.org/wiki/Nature_%28journal%29 Nature], Vol. 518
* [[Ilya Loshchilov]], [[Frank Hutter]] ('''2015'''). ''Online Batch Selection for Faster Training of Neural Networks''. [https://arxiv.org/abs/1511.06343 arXiv:1511.06343]
* [[Yuandong Tian]], [[Yan Zhu]] ('''2015'''). ''Better Computer Go Player with Neural Network and Long-term Prediction''. [http://arxiv.org/abs/1511.06410 arXiv:1511.06410], [http://nuit-blanche.blogspot.de/2016/02/iclr-2016-list-of-accepted-papers.html ICLR 2016] <ref>[http://www.technologyreview.com/view/544181/how-facebooks-ai-researchers-built-a-game-changing-go-engine/?utm_campaign=socialsync&utm_medium=social-post&utm_source=facebook How Facebook’s AI Researchers Built a Game-Changing Go Engine | MIT Technology Review], December 04, 2015</ref> <ref>[http://www.talkchess.com/forum/viewtopic.php?t=58514 Combining Neural Networks and Search techniques (GO)] by Michael Babigian, [[CCC]], December 08, 2015</ref> » [[Go]]
* [[Arvind Neelakantan]], [[Luke Vilnis]], [[Quoc V. Le]], [[Ilya Sutskever]], [[Lukasz Kaiser]], [[Karol Kurach]], [[James Martens]] ('''2015'''). ''Adding Gradient Noise Improves Learning for Very Deep Networks''. [https://arxiv.org/abs/1511.06807 arXiv:1511.06807]

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