https://arxiv.org/pdf/1702.07800.pdf

위 링크의 페이퍼를 봐 줘.


Year
Contributer
Contribution


300 BC
Aristotle
introduced Associationism, started the history of human’s
attempt to understand brain.


1873
Alexander Bain
introduced Neural Groupings as the earliest models of
neural network, inspired Hebbian Learning Rule.


1943
McCulloch & Pitts
introduced MCP Model, which is considered as the
ancestor of Artificial Neural Model.


1949
Donald Hebb
considered as the father of neural networks, introduced
Hebbian Learning Rule, which lays the foundation of
modern neural network.


1958
Frank Rosenblatt
introduced the first perceptron, which highly resembles
modern perceptron.


1974
Paul Werbos
introduced Backpropagation


1980
Teuvo Kohonen
introduced Self Organizing Map
Kunihiko Fukushima
introduced Neocogitron, which inspired Convolutional
Neural Network


1982
John Hopfield
introduced Hopfield Network


1985
Hilton & Sejnowski
introduced Boltzmann Machine


1986
Paul Smolensky
introduced Harmonium, which is later known as Restricted
Boltzmann Machine
Michael I. Jordan
defined and introduced Recurrent Neural Network


1990
Yann LeCun
introduced LeNet, showed the possibility of deep neural
networks in practice


1997
Schuster & Paliwal
introduced Bidirectional Recurrent Neural Network
Hochreiter &
Schmidhuber
introduced LSTM, solved the problem of vanishing
gradient in recurrent neural networks


2006
Geoffrey Hinton
introduced Deep Belief Networks, also introduced
layer-wise pretraining technique, opened current deep
learning era.


2009
Salakhutdinov &
Hinton
introduced Deep Boltzmann Machines


2012
Geoffrey Hinton
introduced Dropout, an efficient way of training neural
networks



그 책은 아마 일본인이 지은 책이라 그런 것 같아.