Geoffrey Hinton
Geoffrey Hinton received his PhD in Artificial Intelligence from Edinburgh in 1978. After five years as a faculty member at Carnegie-Mellon he became a fellow of the Canadian Institute for Advanced Research and moved to the Department of Computer Science at the University of Toronto where he is now an emeritus professor. He is also a VP Engineering fellow at Google and Chief Scientific Adviser at the Vector Institute.
Geoffrey Hinton was one of the researchers who introduced the backpropagation algorithm and the first to use backpropagation for learning word embeddings. His other contributions to neural network research include Boltzmann machines, distributed representations, time-delay neural nets, mixtures of experts, variational learning and deep learning. His research group in Toronto made major breakthroughs in deep learning that revolutionized speech recognition and object classification.
Geoffrey Hinton is a fellow of the UK Royal Society and a foreign member of the US National Academy of Engineering and the American Academy of Arts and Sciences. His awards include the David E. Rumelhart prize, the IJCAI award for research excellence, the Killam prize for Engineering, the IEEE Frank Rosenblatt medal, the NSERC Herzberg Gold Medal, the IEEE James Clerk Maxwell Gold medal, the NEC C&C award, the BBVA award, the Honda Prize and the Turing Award.
- BA (Experimental Psychology), Cambridge University
- PhD (Artificial Intelligence), University of Edinburgh
- Reinforcement learning
- Neural networks
- Optimization
Basic Papers on Deep Learning
- LeCun, Y., Bengio, Y. and Hinton, G. E. (2015) Deep Learning. Nature, Vol. 521, pp 436-444. [pdf]
- Hinton, G. E., Osindero, S. and Teh, Y. (2006) A fast learning algorithm for deep belief nets. Neural Computation, 18, pp 1527-1554. [pdf] Movies of the neural network generating and recognizing digits
- Hinton, G. E. and Salakhutdinov, R. R. (2006) Reducing the dimensionality of data with neural networks. Science, Vol. 313. no. 5786, pp. 504 - 507, 28 July 2006. [ full paper ] [ supporting online material (pdf) ] [ Matlab code ]
Recent Papers
- Hinton, G. E. (2022) The Forward-Forward Algorithm: Some Preliminary Investigations arXiv:2212.13345 [pdf of final version]
Sindy Loewe's translation to python code is available here. - Chen, T., Zhang, R., & Hinton, G. (2022) Analog bits: Generating discrete data using diffusion models with self-conditioning. arXiv preprint arXiv:2208.04202 [pdf]