Yann LeCun
Biographic Data
| ID | 6544714 |
|---|---|
| NAME | Yann LeCun |
| GIVEN NAMES | Yann |
| FAMILY NAME | LeCun |
| SIGNATURE | LECUN Y |
| AFFILIATIONS | AT&T (United States) |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1989 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Learning Abstractions
James Manyika. Yann LeCun is widely considered one of the godfathers of the modern era of artificial intelligence. His pioneering research with Geoffrey Hinton and Yoshua Bengio on deep learning won them the 2018 Turing Award, considered the Nobel Prize for computer science, and in 2025, the three were awarded the Queen Elizabeth Prize for Engineering. Yann has long focused on foundational and scientific advances in AI, from biologically inspired…
L’apprentissage profond, une révolution en intelligence artificielle
Yann LeCun, spécialiste de l’apprentissage automatique des machines (machine learning), est l’un des pères du Deep Learning (apprentissage profond), une méthode à laquelle il se consacre depuis trente ans, malgré le scepticisme qu’il rencontre au départ dans la communauté scientifique. Le Deep Learning, qui fait appel à la fois aux connaissances en neurosciences, aux mathématiques et aux progrès technologiques, est aujourd’hui plébiscité comme un…
Deep learning
Gradient-based learning applied to document recognition
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten charac…
Backpropagation Applied to Handwritten Zip Code Recognition
The ability of learning networks to generalize can be greatly enhanced by providing constraints from the task domain. This paper demonstrates how such constraints can be integrated into a backpropagation network through the architecture of the network. This approach has been successfully applied to the recognition of handwritten zip code digits provided by the U.S. Postal Service. A single network learns the entire recognition operation, going fr…
No prominent works on this page.
Backpropagation Applied to Handwritten Zip Code Recognition
The ability of learning networks to generalize can be greatly enhanced by providing constraints from the task domain. This paper demonstrates how such constraints can be integrated into a backpropagation network through the architecture of the network. This approach has been successfully applied to the recognition of handwritten zip code digits provided by the U.S. Postal Service. A single network learns the entire recognition operation, going fr…
Gradient-based learning applied to document recognition
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten charac…
Deep learning
L’apprentissage profond, une révolution en intelligence artificielle
Yann LeCun, spécialiste de l’apprentissage automatique des machines (machine learning), est l’un des pères du Deep Learning (apprentissage profond), une méthode à laquelle il se consacre depuis trente ans, malgré le scepticisme qu’il rencontre au départ dans la communauté scientifique. Le Deep Learning, qui fait appel à la fois aux connaissances en neurosciences, aux mathématiques et aux progrès technologiques, est aujourd’hui plébiscité comme un…
Learning Abstractions
James Manyika. Yann LeCun is widely considered one of the godfathers of the modern era of artificial intelligence. His pioneering research with Geoffrey Hinton and Yoshua Bengio on deep learning won them the 2018 Turing Award, considered the Nobel Prize for computer science, and in 2025, the three were awarded the Queen Elizabeth Prize for Engineering. Yann has long focused on foundational and scientific advances in AI, from biologically inspired…
Artificial Intelligence (3 works) · Artificial neural network (3 works) · Computer Science (3 works) · Neural Networks and Applications (3 works) · Pattern recognition (psychology) (3 works) · Speech recognition (3 works) · Backpropagation (2 works) · Character recognition (2 works) · Convolutional neural network (2 works) · Deep learning (2 works)