艾力克斯·格雷夫斯 (計算機科學家)

艾力克斯·格雷夫斯
Alex Graves
艾力克斯·格雷夫斯; Alex Graves
母校	愛丁堡大學（BSc）; IDSIA（英语：Dalle Molle Institute for Artificial Intelligence Research）（PhD）
知名于	連接主義時間分類（英语：Connectionist temporal classification）; 神經圖靈機; 可微分神經計算機（英语：Differentiable neural computer）
	科学生涯
研究领域	計算機科學
机构	DeepMind
博士導師	于爾根·施密德胡伯

艾力克斯·格雷夫斯（英語：Alex Graves）是一名計算機科學家。在DeepMind擔任研究科學家之前，他在愛丁堡大學獲得理論物理學學士學位，並在IDSIA（英语：Dalle Molle Institute for Artificial Intelligence Research）的于爾根·施密德胡伯指導下獲得了人工智慧博士學位^[1]。他還曾在慕尼黑工業大學的施密德胡伯和多倫多大學的杰弗里·辛顿手下做過博士後^[2]。

在IDSIA，格雷夫斯通過一種稱為連接主義時間分類（英语：Connectionist temporal classification）（CTC）的新方法訓練長短期記憶神經網路^[3]。這種方法在某些應用中的表現優於傳統的語音識別模型^[4]。2009年，他的CTC訓練的LSTM是第一個贏得模式識別比賽的循環神經網路，並贏得連接手寫識別方面的幾個比賽^[5]^[6]。這種方法已經變得非常流行。Google在智慧型手機上使用CTC訓練的LSTM進行語音識別^[7]^[8]。

格雷夫斯也是神經圖靈機^[9]和密切相關的可微分神經計算機（英语：Differentiable neural computer）的創造者^[10]^[11]。

參考資料

^ Alex Graves. Canadian Institute for Advanced Research. （原始内容存档于1 May 2015）.
^ Marginally Interesting: What is going on with DeepMind and Google?. Blog.mikiobraun.de. 28 January 2014 [May 17, 2016]. （原始内容存档于2016-05-22）.
^ Alex Graves, Santiago Fernandez, Faustino Gomez, and Jürgen Schmidhuber (2006). Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural nets. Proceedings of ICML’06, pp. 369–376.
^ Santiago Fernandez, Alex Graves, and Jürgen Schmidhuber (2007). An application of recurrent neural networks to discriminative keyword spotting. Proceedings of ICANN (2), pp. 220–229.
^ Graves, Alex; and Schmidhuber, Jürgen; Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks, in Bengio, Yoshua; Schuurmans, Dale; Lafferty, John; Williams, Chris K. I.; and Culotta, Aron (eds.), Advances in Neural Information Processing Systems 22 (NIPS'22), December 7th–10th, 2009, Vancouver, BC, Neural Information Processing Systems (NIPS) Foundation, 2009, pp. 545–552
^ A. Graves, M. Liwicki, S. Fernandez, R. Bertolami, H. Bunke, J. Schmidhuber. A Novel Connectionist System for Improved Unconstrained Handwriting Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 5, 2009.
^ Google Research Blog. The neural networks behind Google Voice transcription. August 11, 2015. By Françoise Beaufays http://googleresearch.blogspot.co.at/2015/08/the-neural-networks-behind-google-voice.html （页面存档备份，存于互联网档案馆）
^ Google Research Blog. Google voice search: faster and more accurate. September 24, 2015. By Haşim Sak, Andrew Senior, Kanishka Rao, Françoise Beaufays and Johan Schalkwyk – Google Speech Team http://googleresearch.blogspot.co.uk/2015/09/google-voice-search-faster-and-more.html （页面存档备份，存于互联网档案馆）
^ Google's Secretive DeepMind Startup Unveils a "Neural Turing Machine". [May 17, 2016]. （原始内容存档于2016-08-13）.
^ Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago. Hybrid computing using a neural network with dynamic external memory. Nature. 2016-10-12, 538 (7626): 471–476 [2023-02-23]. Bibcode:2016Natur.538..471G. ISSN 1476-4687. PMID 27732574. S2CID 205251479. doi:10.1038/nature20101. （原始内容存档于2022-10-02）（英语）.
^ Differentiable neural computers | DeepMind. DeepMind. [2016-10-19]. （原始内容存档于2023-07-04）.

[1] Alex Graves. Canadian Institute for Advanced Research. （原始内容存档于1 May 2015）.

[MyUser_Blog.mikiobraun.de_May_17_2016c-2] Marginally Interesting: What is going on with DeepMind and Google?. Blog.mikiobraun.de. 28 January 2014 [May 17, 2016]. （原始内容存档于2016-05-22）.

[graves2006-3] Alex Graves, Santiago Fernandez, Faustino Gomez, and Jürgen Schmidhuber (2006). Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural nets. Proceedings of ICML’06, pp. 369–376.

[fernandez2007keyword-4] Santiago Fernandez, Alex Graves, and Jürgen Schmidhuber (2007). An application of recurrent neural networks to discriminative keyword spotting. Proceedings of ICANN (2), pp. 220–229.

[5] Graves, Alex; and Schmidhuber, Jürgen; Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks, in Bengio, Yoshua; Schuurmans, Dale; Lafferty, John; Williams, Chris K. I.; and Culotta, Aron (eds.), Advances in Neural Information Processing Systems 22 (NIPS'22), December 7th–10th, 2009, Vancouver, BC, Neural Information Processing Systems (NIPS) Foundation, 2009, pp. 545–552

[6] A. Graves, M. Liwicki, S. Fernandez, R. Bertolami, H. Bunke, J. Schmidhuber. A Novel Connectionist System for Improved Unconstrained Handwriting Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 31, no. 5, 2009.

[GoogleVoiceTranscription-7] Google Research Blog. The neural networks behind Google Voice transcription. August 11, 2015. By Françoise Beaufays http://googleresearch.blogspot.co.at/2015/08/the-neural-networks-behind-google-voice.html （页面存档备份，存于互联网档案馆）

[GoogleVoiceSearch-8] Google Research Blog. Google voice search: faster and more accurate. September 24, 2015. By Haşim Sak, Andrew Senior, Kanishka Rao, Françoise Beaufays and Johan Schalkwyk – Google Speech Team http://googleresearch.blogspot.co.uk/2015/09/google-voice-search-faster-and-more.html （页面存档备份，存于互联网档案馆）

[MyUser_Https:_May_17_2016c-9] Google's Secretive DeepMind Startup Unveils a "Neural Turing Machine". [May 17, 2016]. （原始内容存档于2016-08-13）.

[DNCnature2016-10] Graves, Alex; Wayne, Greg; Reynolds, Malcolm; Harley, Tim; Danihelka, Ivo; Grabska-Barwińska, Agnieszka; Colmenarejo, Sergio Gómez; Grefenstette, Edward; Ramalho, Tiago. Hybrid computing using a neural network with dynamic external memory. Nature. 2016-10-12, 538 (7626): 471–476 [2023-02-23]. Bibcode:2016Natur.538..471G. ISSN 1476-4687. PMID 27732574. S2CID 205251479. doi:10.1038/nature20101. （原始内容存档于2022-10-02）（英语）.

[11] Differentiable neural computers | DeepMind. DeepMind. [2016-10-19]. （原始内容存档于2023-07-04）.

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艾力克斯·格雷夫斯 (計算機科學家)

參考資料

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