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Yoshua Bengio
Canadian computer scientist / From Wikipedia, the free encyclopedia
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Yoshua Bengio OC FRS FRSC (born March 5, 1964[1]) is a Canadian computer scientist, most noted for his work on artificial neural networks and deep learning.[2][3][4] He is a professor at the Department of Computer Science and Operations Research at the Université de Montréal and scientific director of the Montreal Institute for Learning Algorithms (MILA).
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Yoshua Bengio |
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Yoshua Bengio in 2019 |
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| Born |
Paris, France |
| Citizenship | Canada |
| Alma mater | McGill University |
| Known for | Deep learning, neural machine translation, generative adversarial networks, “attention model”, word embeddings, denoising auto-encoders, neural language models, learning to learn, Generative Flow Networks (GFlowNets) |
| Awards | Marie-Victorin Prize (2017)
Turing Award (2018) AAAI Fellow (2019) |
| Scientific career | |
| Fields | Computer science |
| Institutions | Université de Montréal |
| Thesis | Artificial Neural Networks and their Application to Sequence Recognition (1991) |
| Doctoral advisor | Renato de Mori |
| Notable students | Ian Goodfellow |
| Website | yoshuabengio.org |
Bengio received the 2018 ACM A.M. Turing Award, together with Geoffrey Hinton and Yann LeCun, for their work in deep learning.[5] Bengio, Hinton, and LeCun, are sometimes referred to as the “Godfathers of AI” and “Godfathers of Deep Learning”.[6][7][8][9][10][11]
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