引用次数
引用: 808,731
H-指数: 181
I10-指数 : 457
出版物: 668
A parallel computation that assigns canonical object-based frames of reference
Geoffrey F. Hinton
international joint conference on artificial intelligence 683 -685
180
1981
Shape representation in parallel systems
Geoffrey F. Hinton
international joint conference on artificial intelligence 1088 -1096
87
1981
Workshop summary: Workshop on learning feature hierarchies
Kay Yu , Ruslan Salakhutdinov , Yann LeCun , Geoff Hinton
Proceedings of the 26th Annual International Conference on Machine Learning - ICML '09 5
2
2009
Convolutional deep belief networks on cifar-10
Alex Krizhevsky , Geoff Hinton
Unpublished manuscript 40 ( 7) 1 -9
712
2010
Deep belief networks
Ruslan Salakhutdinov , Geoff Hinton
Scholarpedia 4 ( 5)
9
2009
Generating Facial Expressions with Deep Belief Nets
Joshua M. , Geoffrey E. , Javier R. , Adam K.
InTech
163
2008
Coaching variables for regression and classification
ROBERT TIBSHIRANI , GEOFFREY HINTON
Statistics and Computing 8 ( 1) 25 -33
26
1998
The development of the time-delayed neural network architecture(Final Report)
GEOFFREY HINTON , JAMESL MCCLELLAND , KEVINJ LANG
1990
RMSprop gradient optimization
Tijmen Tieleman , Geoffery Hinton
URL http://www. cs. toronto. edu/tijmen/csc321/slides/lecture_slides_lec6. pdf
69
2014
On the importance of momentum and initialization in deep learning
Ilya Sutskever , James Martens , George Dahl , Geoffery Hinton
30th International Conference on Machine Learning 404 -439
34
2013
Efficient Stochastic Source Coding and an Application to a Bayesian Network Source Model
Brendan J. Frey , Geoffrey E. Hinton
The Computer Journal 40 157 -165
14
1997
Using relaxation to find a puppet
Geoffrey E. Hinton
Proc. of the AISB Summer Conference 148 -157
27
1976
Learning hierarchical structures with linear relational embedding
Alberto Paccanaro , Geoffrey E Hinton
Advances in neural information processing systems 14: proceedings of the 2001 conference 857 -857
28
2002
Sejnows ki, TJ (1 9 85)
D Hinton Ackley , GA Hinton
A learning algorithm for Bolt z mann machines. D og $ iti а 147 -16
16
Distilling the knowledge in a neural network [EB/OL]
G HINTON , O VINYALS , J DEAN
3
10
2015
WJ CLANCEY
MA AIZERMAN , S AMAREL , HG BARROW , H BERLINER
Daniel G. BOBROW Xerox Corporation
AG COHN , LC AIELLO , Y ANZAI , RK BAJCSY
R. DAVIS Al Lab, MIT Cambridge, MA, USA
R DECHTER , R MOORE , S MUGGLETON , J DE KLEER
JG CARBONELL Carnegie-Mellon llniversity Pittsburgh, PA, USA
AG COHN , LC AIELLO , Y ANZAI , RK BAJCSY
JG CARBONELL
S AMAREL , Y ANZAI , H BERLINER , RS BOYER