Geoffrey Hinton
Geoff Hinton | |
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Born | Geoffrey Everest Hinton 6 December 1947 [1] Wimbledon, London |
Residence | Canada |
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Thesis | Relaxation and its role in vision (1977) |
Doctoral advisor | H. Christopher Longuet-Higgins[3][4][5] |
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Website www |
Geoffrey Everest Hinton FRS[6] (born 6 December 1947) is a British-born cognitive psychologist and computer scientist, most noted for his work on artificial neural networks. As of 2015[update] he divides his time working for Google and University of Toronto.[7] He was one of the first researchers who demonstrated the use of generalized backpropagation algorithm for training multi-layer neural nets and is an important figure in the deep learning movement.[8][9][10]
Education
Hinton was educated at King's College, Cambridge graduating in 1970, with a Bachelor of Arts in experimental psychology.[1] He continued his study at the University of Edinburgh where he was awarded a PhD in artificial intelligence in 1977 for research supervised by H. Christopher Longuet-Higgins.[3][11]
Career
He has worked at Sussex, University of California San Diego, Cambridge, Carnegie Mellon University and University College London. He was the founding director of the Gatsby Computational Neuroscience Unit at University College London, and is currently a professor in the computer science department at the University of Toronto. He holds a Canada Research Chair in Machine Learning. He is the director of the program on "Neural Computation and Adaptive Perception" which is funded by the Canadian Institute for Advanced Research. Hinton taught a free online course on Neural Networks on the education platform Coursera in 2012.[12] Hinton joined Google in March 2013 when his company, DNNresearch Inc, was acquired. He is planning to "divide his time between his university research and his work at Google".[13]
Research
An accessible introduction to Geoffrey Hinton's research can be found in his articles in Scientific American in September 1992 and October 1993. He investigates ways of using neural networks for learning, memory, perception and symbol processing and has authored over 200 publications[14][2] in these areas. He was one of the first researchers who demonstrated the use of generalized back-propagation algorithm for training multi-layer neural networks that has been widely used for practical applications. He co-invented Boltzmann machines with Terry Sejnowski. His other contributions to neural network research include distributed representations, time delay neural network, mixtures of experts, Helmholtz machines and Product of Experts. His current[when?] main interest is in unsupervised learning procedures for neural networks with rich sensory input.[citation needed]
Honours and awards
Hinton was elected a Fellow of the Royal Society (FRS) in 1998.[6][15] Hinton was the first winner of the David E. Rumelhart Prize.[when?] His certificate of election for the Royal Society reads: <templatestyles src="Template:Blockquote/styles.css" />
Geoffrey E. Hinton is internationally distinguished for his work on artificial neural nets, especially how they can be designed to learn without the aid of a human teacher. This may will be the start of autonomous intelligent brain-like machines. He has compared effects of brain damage with effects of losses in such a net, and found striking similarities with human impairment, such as for recognition of names and losses of categorization. His work includes studies of mental imagery, and inventing puzzles for testing originality and creative intelligence. It is conceptual, mathematically sophisticated and experimental. He brings these skills together with striking effect to produce important work of great interest.[16]
In 2001, Hinton was awarded an Honorary Doctorate from the University of Edinburgh.
Hinton was the 2005 recipient of the IJCAI Award for Research Excellence lifetime-achievement award.
He has also been awarded the 2011 Herzberg Canada Gold Medal for Science and Engineering.[17]
In 2013, Hinton was awarded an Honorary Doctorate from the Université de Sherbrooke.
Personal life
Hinton is the great-great-grandson both of logician George Boole whose work eventually became one of the foundations of modern computer science, and of surgeon and author James Hinton.[18] His father is Howard Hinton.[19]
References
- ↑ 1.0 1.1 Lua error in package.lua at line 80: module 'strict' not found. (subscription required)
- ↑ 2.0 2.1 Geoffrey Hinton's publications indexed by Google Scholar, a service provided by Google
- ↑ 3.0 3.1 3.2 Geoffrey Hinton at the Mathematics Genealogy Project
- ↑ Geoffrey E. Hinton's Academic Genealogy
- ↑ Lua error in package.lua at line 80: module 'strict' not found.
- ↑ 6.0 6.1 6.2 Lua error in package.lua at line 80: module 'strict' not found.
- ↑ Lua error in package.lua at line 80: module 'strict' not found.
- ↑ "How a Toronto professor’s research revolutionized artificial intelligence". Toronto Star, Kate Allen, Apr 17 2015
- ↑ "The Next Generation of Neural Networks" on YouTube
- ↑ AMA Geoffrey Hinton (self.MachineLearning) www.reddit.com Ask Me Anything : Geoffrey Hinton
- ↑ Lua error in package.lua at line 80: module 'strict' not found.
- ↑ https://www.coursera.org/course/neuralnets
- ↑ Lua error in package.lua at line 80: module 'strict' not found.
- ↑ Geoffrey Hinton's publications indexed by the Scopus bibliographic database, a service provided by Elsevier.
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- ↑ The Isaac Newton of logic
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- Artificial intelligence researchers
- British computer scientists
- Canadian computer scientists
- Cognitive scientists
- Fellows of the Association for the Advancement of Artificial Intelligence
- Fellows of the Royal Society
- Google employees
- Living people
- Machine learning researchers
- University of Toronto faculty
- Canada Research Chairs
- 1947 births
- Carnegie Mellon University faculty
- Rumelhart Prize laureates
- Alumni of the University of Edinburgh