Geoffrey Hinton

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George E. DahlGoogle Inc.Potvrđena adresa e-pošte na google.com
Terrence SejnowskiFrancis Crick Professor, Salk Institute, Distingished Professor, UC San DiegoPotvrđena adresa e-pošte na salk.edu
Vinod NairResearch Scientist, DeepMindPotvrđena adresa e-pošte na google.com
Abdelrahman MohamedResearch scientist, Facebook AI ResearchPotvrđena adresa e-pošte na fb.com
Radford NealU Toronto *** GOOGLE SCHOLAR CAN GIVE WRONG PUBLICATION DATE/REFERENCE - LOOK AT ACTUAL PAPER/BOOK!Potvrđena adresa e-pošte na utstat.toronto.edu
Sidney FelsProfessor of Electrical and Computer Engineering, University of British ColumbiaPotvrđena adresa e-pošte na ece.ubc.ca
David C. PlautProfessor of Psychology, Carnegie Mellon UniversityPotvrđena adresa e-pošte na cmu.edu
Chris WilliamsProfessor of Machine Learning, University of EdinburghPotvrđena adresa e-pošte na inf.ed.ac.uk
Demetri TerzopoulosDistinguished Professor & Chancellor's Professor of Computer Science, UCLAPotvrđena adresa e-pošte na cs.ucla.edu
Robert TibshiraniProfessor of Biomedical Data Sciences, and of Statistics, Stanford UniversityPotvrđena adresa e-pošte na stanford.edu
Steven L. SmallUniversity of Texas at DallasPotvrđena adresa e-pošte na utdallas.edu

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Geoffrey Hinton

Emeritus Prof. Computer Science, University of Toronto

Potvrđena adresa e-pošte na cs.toronto.edu - Početna stranica

machine learning psychology artificial intelligence cognitive science computer science


Naslov Poredaj po navodima Poredaj po godini Poredaj po naslovu	Citirano Citirano	Godina
Imagenet classification with deep convolutional neural networks A Krizhevsky, I Sutskever, GE Hinton Advances in neural information processing systems 25, 2012	173685*	2012
Deep learning Y LeCun, Y Bengio, G Hinton Nature 521 (7553), 436-44, 2015	92944	2015
Learning internal representations by error-propagation DE Rumelhart, GE Hinton, RJ Williams Parallel Distributed Processing: Explorations in the Microstructure of …, 1986	59617*	1986
Dropout: a simple way to prevent neural networks from overfitting N Srivastava, G Hinton, A Krizhevsky, I Sutskever, R Salakhutdinov The journal of machine learning research 15 (1), 1929-1958, 2014	55926	2014
Visualizing data using t-SNE L van der Maaten, G Hinton Journal of Machine Learning Research 9 (Nov), 2579-2605, 2008	55500	2008
Learning representations by back-propagating errors DE Rumelhart, GE Hinton, RJ Williams Nature 323 (6088), 533-536, 1986	42143	1986
Learning multiple layers of features from tiny images A Krizhevsky, G Hinton	35766	2009
Rectified linear units improve restricted boltzmann machines V Nair, GE Hinton Proceedings of the 27th international conference on machine learning (ICML …, 2010	27309	2010
Reducing the dimensionality of data with neural networks GE Hinton, RR Salakhutdinov Science 313 (5786), 504-507, 2006	24716	2006
Distilling the knowledge in a neural network G Hinton, O Vinyals, J Dean arXiv preprint arXiv:1503.02531, 2015	24102	2015
A simple framework for contrastive learning of visual representations T Chen, S Kornblith, M Norouzi, G Hinton International conference on machine learning, 1597-1607, 2020	22863	2020
A fast learning algorithm for deep belief nets GE Hinton, S Osindero, YW Teh Neural computation 18 (7), 1527-1554, 2006	22631	2006
Layer normalization JL Ba, JR Kiros, GE Hinton arXiv preprint arXiv:1607.06450, 2016	14741	2016
Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups G Hinton, L Deng, D Yu, GE Dahl, A Mohamed, N Jaitly, A Senior, ... IEEE Signal processing magazine 29 (6), 82-97, 2012	14236	2012
Speech recognition with deep recurrent neural networks A Graves, A Mohamed, G Hinton 2013 IEEE international conference on acoustics, speech and signal …, 2013	12179	2013
Improving neural networks by preventing co-adaptation of feature detectors GE Hinton, N Srivastava, A Krizhevsky, I Sutskever, RR Salakhutdinov arXiv preprint arXiv:1207.0580, 2012	12010	2012
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude T Tieleman, G Hinton Coursera: Neural networks for machine learning, 2012	8391	2012
Schemata and sequential thought processes in PDP models. D Rumelhart, P Smolenksy, J McClelland, G Hinton Parallel distributed processing: Explorations in the microstructure of …, 1986	7610*	1986
Advances in neural information processing systems 22 DD Lee, P Pham, Y Largman, A Ng Tech Rep, 2009	7586*	2009
On the importance of initialization and momentum in deep learning I Sutskever, J Martens, G Dahl, G Hinton International conference on machine learning, 1139-1147, 2013	6792	2013

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