Geoffrey E. Hinton

Department of Computer Science, University of Toronto

	2012
156		Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton: Conditional Restricted Boltzmann Machines for Structured Output Prediction CoRR abs/1202.3748: (2012)
155		Graham W. Taylor, Geoffrey E. Hinton: Products of Hidden Markov Models: It Takes N>1 to Tango CoRR abs/1205.2614: (2012)
154		Abdel-rahman Mohamed, George E. Dahl, Geoffrey E. Hinton: Acoustic Modeling Using Deep Belief Networks. IEEE Transactions on Audio, Speech & Language Processing 20(1): 14-22 (2012)
153		Dong Yu, Geoffrey E. Hinton, Nelson Morgan, Jen-Tzung Chien, Shigeki Sagayama: Introduction to the Special Section on Deep Learning for Speech and Language Processing. IEEE Transactions on Audio, Speech & Language Processing 20(1): 4-6 (2012)
152		Laurens van der Maaten, Geoffrey E. Hinton: Visualizing non-metric similarities in multiple maps. Machine Learning 87(1): 33-55 (2012)
	2011
151		Joshua Susskind, Geoffrey E. Hinton, Roland Memisevic, Marc Pollefeys: Modeling the joint density of two images under a variety of transformations. CVPR 2011: 2793-2800
150		Marc'Aurelio Ranzato, Joshua Susskind, Volodymyr Mnih, Geoffrey E. Hinton: On deep generative models with applications to recognition. CVPR 2011: 2857-2864
149		Alex Krizhevsky, Geoffrey E. Hinton: Using very deep autoencoders for content-based image retrieval. ESANN 2011
148		Geoffrey E. Hinton, Alex Krizhevsky, Sida D. Wang: Transforming Auto-Encoders. ICANN (1) 2011: 44-51
147		Abdel-rahman Mohamed, Tara N. Sainath, George E. Dahl, Bhuvana Ramabhadran, Geoffrey E. Hinton, Michael A. Picheny: Deep Belief Networks using discriminative features for phone recognition. ICASSP 2011: 5060-5063
146		Ruhi Sarikaya, Geoffrey E. Hinton, Bhuvana Ramabhadran: Deep belief nets for natural language call-routing. ICASSP 2011: 5680-5683
145		Navdeep Jaitly, Geoffrey E. Hinton: Learning a better representation of speech soundwaves using restricted boltzmann machines. ICASSP 2011: 5884-5887
144		Ilya Sutskever, James Martens, Geoffrey E. Hinton: Generating Text with Recurrent Neural Networks. ICML 2011: 1017-1024
143		Volodymyr Mnih, Hugo Larochelle, Geoffrey E. Hinton: Conditional Restricted Boltzmann Machines for Structured Output Prediction. UAI 2011: 514-522
142		Geoffrey E. Hinton: A better way to learn features: technical perspective. Commun. ACM 54(10): 94 (2011)
141		Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis: Two Distributed-State Models For Generating High-Dimensional Time Series. Journal of Machine Learning Research 12: 1025-1068 (2011)
	2010
140		Marc'Aurelio Ranzato, Geoffrey E. Hinton: Modeling pixel means and covariances using factorized third-order boltzmann machines. CVPR 2010: 2551-2558
139		Graham W. Taylor, Leonid Sigal, David J. Fleet, Geoffrey E. Hinton: Dynamical binary latent variable models for 3D human pose tracking. CVPR 2010: 631-638
138		Volodymyr Mnih, Geoffrey E. Hinton: Learning to Detect Roads in High-Resolution Aerial Images. ECCV (6) 2010: 210-223
137		Abdel-rahman Mohamed, Geoffrey E. Hinton: Phone recognition using Restricted Boltzmann Machines. ICASSP 2010: 4354-4357
136		Vinod Nair, Geoffrey E. Hinton: Rectified Linear Units Improve Restricted Boltzmann Machines. ICML 2010: 807-814
135		Li Deng, Michael L. Seltzer, Dong Yu, Alex Acero, Abdel-rahman Mohamed, Geoffrey E. Hinton: Binary coding of speech spectrograms using a deep auto-encoder. INTERSPEECH 2010: 1692-1695
134		Hugo Larochelle, Geoffrey E. Hinton: Learning to combine foveal glimpses with a third-order Boltzmann machine. NIPS 2010: 1243-1251
133		Roland Memisevic, Christopher Zach, Geoffrey E. Hinton, Marc Pollefeys: Gated Softmax Classification. NIPS 2010: 1603-1611
132		Marc'Aurelio Ranzato, Volodymyr Mnih, Geoffrey E. Hinton: Generating more realistic images using gated MRF's. NIPS 2010: 2002-2010
131		George E. Dahl, Marc'Aurelio Ranzato, Abdel-rahman Mohamed, Geoffrey E. Hinton: Phone Recognition with the Mean-Covariance Restricted Boltzmann Machine. NIPS 2010: 469-477
130		Geoffrey E. Hinton: Boltzmann Machines. Encyclopedia of Machine Learning 2010: 132-136
129		Geoffrey E. Hinton: Deep Belief Nets. Encyclopedia of Machine Learning 2010: 267-269
128		Marc'Aurelio Ranzato, Alex Krizhevsky, Geoffrey E. Hinton: Factored 3-Way Restricted Boltzmann Machines For Modeling Natural Images. Journal of Machine Learning Research - Proceedings Track 9: 621-628 (2010)
127		Tanya Schmah, Grigori Yourganov, Richard S. Zemel, Geoffrey E. Hinton, Steven L. Small, Stephen C. Strother: Comparing Classification Methods for Longitudinal fMRI Studies. Neural Computation 22(11): 2729-2762 (2010)
126		Roland Memisevic, Geoffrey E. Hinton: Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines. Neural Computation 22(6): 1473-1492 (2010)
125		Ilya Sutskever, Geoffrey E. Hinton: Temporal-Kernel Recurrent Neural Networks. Neural Networks 23(2): 239-243 (2010)
	2009
124		Nicolas Heess, Christopher K. I. Williams, Geoffrey E. Hinton: Learning Generative Texture Models with extended Fields-of-Experts. BMVC 2009
123		Matthew D. Zeiler, Graham W. Taylor, Nikolaus F. Troje, Geoffrey E. Hinton: Modeling pigeon behavior using a Conditional Restricted Boltzmann Machine. ESANN 2009
122		Graham W. Taylor, Geoffrey E. Hinton: Factored conditional restricted Boltzmann Machines for modeling motion style. ICML 2009: 129
121		Tijmen Tieleman, Geoffrey E. Hinton: Using fast weights to improve persistent contrastive divergence. ICML 2009: 130
120		Kay Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio: Workshop summary: Workshop on learning feature hierarchies. ICML 2009: 165
119		Vinod Nair, Geoffrey E. Hinton: 3D Object Recognition with Deep Belief Nets. NIPS 2009: 1339-1347
118		Mark Palatucci, Dean Pomerleau, Geoffrey E. Hinton, Tom M. Mitchell: Zero-shot Learning with Semantic Output Codes. NIPS 2009: 1410-1418
117		Ruslan Salakhutdinov, Geoffrey E. Hinton: Replicated Softmax: an Undirected Topic Model. NIPS 2009: 1607-1614
116		Graham W. Taylor, Geoffrey E. Hinton: Products of Hidden Markov Models: It Takes N>1 to Tango. UAI 2009: 522-529
115		Ruslan Salakhutdinov, Geoffrey E. Hinton: Semantic hashing. Int. J. Approx. Reasoning 50(7): 969-978 (2009)
114		Ruslan Salakhutdinov, Geoffrey E. Hinton: Deep Boltzmann Machines. Journal of Machine Learning Research - Proceedings Track 5: 448-455 (2009)
113		Andriy Mnih, Zhang Yuecheng, Geoffrey E. Hinton: Improving a statistical language model through non-linear prediction. Neurocomputing 72(7-9): 1414-1418 (2009)
112		Geoffrey E. Hinton: Deep belief networks. Scholarpedia 4(5): 5947 (2009)
	2008
111		Zhang Yuecheng, Andriy Mnih, Geoffrey E. Hinton: Improving a statistical language model by modulating the effects of context words. ESANN 2008: 493-498
110		Vinod Nair, Joshua Susskind, Geoffrey E. Hinton: Analysis-by-Synthesis by Learning to Invert Generative Black Boxes. ICANN (1) 2008: 971-981
109		Andriy Mnih, Geoffrey E. Hinton: A Scalable Hierarchical Distributed Language Model. NIPS 2008: 1081-1088
108		Vinod Nair, Geoffrey E. Hinton: Implicit Mixtures of Restricted Boltzmann Machines. NIPS 2008: 1145-1152
107		Tanya Schmah, Geoffrey E. Hinton, Richard S. Zemel, Steven L. Small, Stephen C. Strother: Generative versus discriminative training of RBMs for classification of fMRI images. NIPS 2008: 1409-1416
106		Ilya Sutskever, Geoffrey E. Hinton: Using matrices to model symbolic relationship. NIPS 2008: 1593-1600
105		Ilya Sutskever, Geoffrey E. Hinton, Graham W. Taylor: The Recurrent Temporal Restricted Boltzmann Machine. NIPS 2008: 1601-1608
104		Ilya Sutskever, Geoffrey E. Hinton: Deep, Narrow Sigmoid Belief Networks Are Universal Approximators. Neural Computation 20(11): 2629-2636 (2008)
	2007
103		Roland Memisevic, Geoffrey E. Hinton: Unsupervised Learning of Image Transformations. CVPR 2007
102		Andriy Mnih, Geoffrey E. Hinton: Three new graphical models for statistical language modelling. ICML 2007: 641-648
101		Ruslan Salakhutdinov, Andriy Mnih, Geoffrey E. Hinton: Restricted Boltzmann machines for collaborative filtering. ICML 2007: 791-798
100		Simon Osindero, Geoffrey E. Hinton: Modeling image patches with a directed hierarchy of Markov random fields. NIPS 2007
99		Ruslan Salakhutdinov, Geoffrey E. Hinton: Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes. NIPS 2007
98		Ruslan Salakhutdinov, Geoffrey E. Hinton: Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure. Journal of Machine Learning Research - Proceedings Track 2: 412-419 (2007)
97		Ilya Sutskever, Geoffrey E. Hinton: Learning Multilevel Distributed Representations for High-Dimensional Sequences. Journal of Machine Learning Research - Proceedings Track 2: 548-555 (2007)
96		James Cook, Ilya Sutskever, Andriy Mnih, Geoffrey E. Hinton: Visualizing Similarity Data with a Mixture of Maps. Journal of Machine Learning Research - Proceedings Track 2: 67-74 (2007)
95		Geoffrey E. Hinton: Boltzmann machine. Scholarpedia 2(5): 1668 (2007)
	2006
94		Graham W. Taylor, Geoffrey E. Hinton, Sam T. Roweis: Modeling Human Motion Using Binary Latent Variables. NIPS 2006: 1345-1352
93		Geoffrey E. Hinton, Simon Osindero, Max Welling, Yee Whye Teh: Unsupervised Discovery of Nonlinear Structure Using Contrastive Backpropagation. Cognitive Science 30(4): 725-731 (2006)
92		Simon Osindero, Max Welling, Geoffrey E. Hinton: Topographic Product Models Applied to Natural Scene Statistics. Neural Computation 18(2): 381-414 (2006)
91		Geoffrey E. Hinton, Simon Osindero, Yee Whye Teh: A Fast Learning Algorithm for Deep Belief Nets. Neural Computation 18(7): 1527-1554 (2006)
	2005
90		Geoffrey E. Hinton: What kind of graphical model is the brain? IJCAI 2005: 1765-
89		Geoffrey E. Hinton, Vinod Nair: Inferring Motor Programs from Images of Handwritten Digits. NIPS 2005
88		Roland Memisevic, Geoffrey E. Hinton: Improving dimensionality reduction with spectral gradient descent. Neural Networks 18(5-6): 702-710 (2005)
	2004
87		Max Welling, Michal Rosen-Zvi, Geoffrey E. Hinton: Exponential Family Harmoniums with an Application to Information Retrieval. NIPS 2004
86		Roland Memisevic, Geoffrey E. Hinton: Multiple Relational Embedding. NIPS 2004
85		Jacob Goldberger, Sam T. Roweis, Geoffrey E. Hinton, Ruslan Salakhutdinov: Neighbourhood Components Analysis. NIPS 2004
84		Max Welling, Richard S. Zemel, Geoffrey E. Hinton: Probabilistic sequential independent components analysis. IEEE Transactions on Neural Networks 15(4): 838-849 (2004)
83		Brian Sallans, Geoffrey E. Hinton: Reinforcement Learning with Factored States and Actions. Journal of Machine Learning Research 5: 1063-1088 (2004)
	2003
82		Geoffrey E. Hinton, Max Welling, Andriy Mnih: Wormholes Improve Contrastive Divergence. NIPS 2003
81		Max Welling, Richard S. Zemel, Geoffrey E. Hinton: Efficient Parametric Projection Pursuit Density Estimation. UAI 2003: 575-582
80		Yee Whye Teh, Max Welling, Simon Osindero, Geoffrey E. Hinton: Energy-Based Models for Sparse Overcomplete Representations. Journal of Machine Learning Research 4: 1235-1260 (2003)
	2002
79		Sageev Oore, Demetri Terzopoulos, Geoffrey E. Hinton: A Desktop Input Device and Interface for Interactive 3D Character Animation. Graphics Interface 2002: 133-140
78		Max Welling, Geoffrey E. Hinton: A New Learning Algorithm for Mean Field Boltzmann Machines. ICANN 2002: 351-357
77		Max Welling, Geoffrey E. Hinton, Simon Osindero: Learning Sparse Topographic Representations with Products of Student-t Distributions. NIPS 2002: 1359-1366
76		Max Welling, Richard S. Zemel, Geoffrey E. Hinton: Self Supervised Boosting. NIPS 2002: 665-672
75		Geoffrey E. Hinton, Sam T. Roweis: Stochastic Neighbor Embedding. NIPS 2002: 833-840
74		Fiora Pirri, Geoffrey E. Hinton, Hector J. Levesque: In Memory of Ray Reiter (1939-2002). AI Magazine 23(4): 93 (2002)
73		Sageev Oore, Demetri Terzopoulos, Geoffrey E. Hinton: Local Physical Models for Interactive Character Animation. Comput. Graph. Forum 21(3): 337-346 (2002)
72		Guy Mayraz, Geoffrey E. Hinton: Recognizing Handwritten Digits Using Hierarchical Products of Experts. IEEE Trans. Pattern Anal. Mach. Intell. 24(2): 189-197 (2002)
71		Geoffrey E. Hinton: Training Products of Experts by Minimizing Contrastive Divergence. Neural Computation 14(8): 1771-1800 (2002)
	2001
70		Andrew D. Brown, Geoffrey E. Hinton: Relative Density Nets: A New Way to Combine Backpropagation with HMM's. NIPS 2001: 1149-1156
69		Alberto Paccanaro, Geoffrey E. Hinton: Learning Hierarchical Structures with Linear Relational Embedding. NIPS 2001: 857-864
68		Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinton: Global Coordination of Local Linear Models. NIPS 2001: 889-896
67		Geoffrey E. Hinton, Yee Whye Teh: Discovering Multiple Constraints that are Frequently Approximately Satisfied. UAI 2001: 227-234
66		Alberto Paccanaro, Geoffrey E. Hinton: Learning Distributed Representations of Concepts Using Linear Relational Embedding. IEEE Trans. Knowl. Data Eng. 13(2): 232-244 (2001)
	2000
65		Geoffrey E. Hinton: Modeling High-Dimensional Data by Combining Simple Experts. AAAI/IAAI 2000: 1159-1164
64		Alberto Paccanaro, Geoffrey E. Hinton: Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space. ICML 2000: 711-718
63		Alberto Paccanaro, Geoffrey E. Hinton: Extracting Distributed Representations of Concepts and Relations from Positive and Negative Propositions. IJCNN (2) 2000: 259-264
62		Brian Sallans, Geoffrey E. Hinton: Using Free Energies to Represent Q-values in a Multiagent Reinforcement Learning Task. NIPS 2000: 1075-1081
61		Yee Whye Teh, Geoffrey E. Hinton: Rate-coded Restricted Boltzmann Machines for Face Recognition. NIPS 2000: 908-914
60		Guy Mayraz, Geoffrey E. Hinton: Recognizing Hand-written Digits Using Hierarchical Products of Experts. NIPS 2000: 953-959
59		Zoubin Ghahramani, Geoffrey E. Hinton: Variational Learning for Switching State-Space Models. Neural Computation 12(4): 831-864 (2000)
58		Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. Neural Computation 12(9): 2109-2128 (2000)
57		Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates. VLSI Signal Processing 26(1-2): 133-140 (2000)
	1999
56		Geoffrey E. Hinton, Andrew D. Brown: Spiking Boltzmann Machines. NIPS 1999: 122-128
55		Geoffrey E. Hinton, Zoubin Ghahramani, Yee Whye Teh: Learning to Parse Images. NIPS 1999: 463-469
54		Brendan J. Frey, Geoffrey E. Hinton: Variational Learning in Nonlinear Gaussian Belief Networks. Neural Computation 11(1): 193-213 (1999)
	1998
53		Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. NIPS 1998: 599-605
52		Radek Grzeszczuk, Demetri Terzopoulos, Geoffrey E. Hinton: Fast Neural Network Emulation of Dynamical Systems for Computer Animation. NIPS 1998: 882-888
51		Radek Grzeszczuk, Demetri Terzopoulos, Geoffrey E. Hinton: NeuroAnimator: Fast Neural Network Emulation and Control of Physics-based Models. SIGGRAPH 1998: 9-20
50		S. Sidney Fels, Geoffrey E. Hinton: Glove-TalkII-a neural-network interface which maps gestures to parallel formant speech synthesizer controls. IEEE Transactions on Neural Networks 9(1): 205-212 (1998)
	1997
49		Zoubin Ghahramani, Geoffrey E. Hinton: Hierarchical Non-linear Factor Analysis and Topographic Maps. NIPS 1997
48		Brendan J. Frey, Geoffrey E. Hinton: Efficient Stochastic Source Coding and an Application to a Bayesian Network Source Model. Comput. J. 40(2/3): 157-165 (1997)
47		Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton: Instantiating Deformable Models with a Neural Net. Computer Vision and Image Understanding 68(1): 120-126 (1997)
46		Peter Dayan, Geoffrey E. Hinton: Using Expectation-Maximization for Reinforcement Learning. Neural Computation 9(2): 271-278 (1997)
45		Sageev Oore, Geoffrey E. Hinton, Gregory Dudek: A Mobile Robot that Learns its Place. Neural Computation 9(3): 683-699 (1997)
	1996
44		Brendan J. Frey, Geoffrey E. Hinton: Free Energy Coding. Data Compression Conference 1996: 73-81
43		Michael Revow, Christopher K. I. Williams, Geoffrey E. Hinton: Using Generative Models for Handwritten Digit Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 18(6): 592-606 (1996)
42		Peter Dayan, Geoffrey E. Hinton: Varieties of Helmholtz Machine. Neural Networks 9(8): 1385-1403 (1996)
	1995
41		Sidney Fels, Geoffrey E. Hinton: GloveTalkII: An Adaptive Gesture-to-Formant Interface. CHI 1995: 456-463
40		Geoffrey E. Hinton, Michael Revow: Using Pairs of Data-Points to Define Splits for Decision Trees. NIPS 1995: 507-513
39		Brendan J. Frey, Geoffrey E. Hinton, Peter Dayan: Does the Wake-sleep Algorithm Produce Good Density Estimators? NIPS 1995: 661-667
38		Peter Dayan, Geoffrey E. Hinton, Radford M. Neal, Richard S. Zemel: The Helmholtz machine. Neural Computation 7(5): 889-904 (1995)
	1994
37		Geoffrey E. Hinton, Michael Revow, Peter Dayan: Recognizing Handwritten Digits Using Mixtures of Linear Models. NIPS 1994: 1015-1022
36		Lei Xu, Michael I. Jordan, Geoffrey E. Hinton: An Alternative Model for Mixtures of Experts. NIPS 1994: 633-640
35		Sidney Fels, Geoffrey E. Hinton: Glove-TalkII: Mapping Hand Gestures to Speech Using Neural Networks. NIPS 1994: 843-850
34		Christopher K. I. Williams, Michael Revow, Geoffrey E. Hinton: Using a neural net to instantiate a deformable model. NIPS 1994: 965-972
	1993
33		Geoffrey E. Hinton, Drew van Camp: Keeping the Neural Networks Simple by Minimizing the Description Length of the Weights. COLT 1993: 5-13
32		Richard S. Zemel, Geoffrey E. Hinton: Developing Population Codes by Minimizing Description Length. NIPS 1993: 11-18
31		Geoffrey E. Hinton, Richard S. Zemel: Autoencoders, Minimum Description Length and Helmholtz Free Energy. NIPS 1993: 3-10
30		Suzanna Becker, Geoffrey E. Hinton: Learning Mixture Models of Spatial Coherence. Neural Computation 5(2): 267-277 (1993)
	1992
29		Peter Dayan, Geoffrey E. Hinton: Feudal Reinforcement Learning. NIPS 1992: 271-278
28		Steven J. Nowlan, Geoffrey E. Hinton: Simplifying Neural Networks by Soft Weight-Sharing. Neural Computation 4(4): 473-493 (1992)
	1991
27		Suzanna Becker, Geoffrey E. Hinton: Learning to Make Coherent Predictions in Domains with Discontinuities. NIPS 1991: 372-379
26		Geoffrey E. Hinton, Christopher K. I. Williams, Michael Revow: Adaptive Elastic Models for Hand-Printed Character Recognition. NIPS 1991: 512-519
25		Steven J. Nowlan, Geoffrey E. Hinton: Adaptive Soft Weight Tying using Gaussian Mixtures. NIPS 1991: 993-1000
	1990
24		Sidney Fels, Geoffrey E. Hinton: Building adaptive interfaces with neural networks: The glove-talk pilot study. INTERACT 1990: 683-688
23		Richard S. Zemel, Geoffrey E. Hinton: Discovering Viewpoint-Invariant Relationships That Characterize Objects. NIPS 1990: 299-305
22		Steven J. Nowlan, Geoffrey E. Hinton: Evaluation of Adaptive Mixtures of Competing Experts. NIPS 1990: 774-780
21		Geoffrey E. Hinton: Connectionist Symbol Processing - Preface. Artif. Intell. 46(1-2): 1-4 (1990)
20		Geoffrey E. Hinton: Mapping Part-Whole Hierarchies into Connectionist Networks. Artif. Intell. 46(1-2): 47-75 (1990)
19		Kevin J. Lang, Alex Waibel, Geoffrey E. Hinton: A time-delay neural network architecture for isolated word recognition. Neural Networks 3(1): 23-43 (1990)
	1989
18		Kevin J. Lang, Geoffrey E. Hinton: Dimensionality Reduction and Prior Knowledge in E-Set Recognition. NIPS 1989: 178-185
17		Richard S. Zemel, Michael Mozer, Geoffrey E. Hinton: TRAFFIC: Recognizing Objects Using Hierarchical Reference Frame Transformations. NIPS 1989: 266-273
16		Conrad C. Galland, Geoffrey E. Hinton: Discovering High Order Features with Mean Field Modules. NIPS 1989: 509-515
15		Geoffrey E. Hinton: Connectionist Learning Procedures. Artif. Intell. 40(1-3): 185-234 (1989)
	1988
14		Yann LeCun, Conrad C. Galland, Geoffrey E. Hinton: GEMINI: Gradient Estimation Through Matrix Inversion After Noise Injection. NIPS 1988: 141-148
13		David S. Touretzky, Geoffrey E. Hinton: A Distributed Connectionist Production System. Cognitive Science 12(3): 423-466 (1988)
	1987
12		Geoffrey E. Hinton, James L. McClelland: Learning Representations by Recirculation. NIPS 1987: 358-366
11		Geoffrey E. Hinton: Learning Translation Invariant Recognition in Massively Parallel Networks. PARLE (1) 1987: 1-13
10		Scott E. Fahlman, Geoffrey E. Hinton: Connectionist Architectures for Artificial Intelligence. IEEE Computer 20(1): 100-109 (1987)
	1986
9		Drew V. McDermott, Geoffrey E. Hinton: Learning in Massively Parallel Nets (Panel). AAAI 1986: 1149
	1985
8		David S. Touretzky, Geoffrey E. Hinton: Symbols Among the Neurons: Details of a Connectionist Inference Architecture. IJCAI 1985: 238-243
7		Geoffrey E. Hinton, Kevin J. Lang: Shape Recognition and Illusory Conjunctions. IJCAI 1985: 252-259
6		David H. Ackley, Geoffrey E. Hinton, Terrence J. Sejnowski: A Learning Algorithm for Boltzmann Machines. Cognitive Science 9(1): 147-169 (1985)
	1983
5		Scott E. Fahlman, Geoffrey E. Hinton, Terrence J. Sejnowski: Massively Parallel Architectures for AI: NETL, Thistle, and Boltzmann Machines. AAAI 1983: 109-113
	1981
4		Geoffrey E. Hinton: Shape Representation in Parallel Systems. IJCAI 1981: 1088-1096
3		Geoffrey E. Hinton: A Parallel Computation that Assigns Canonical Object-Based Frames of Reference. IJCAI 1981: 683-685
	1978
2		Aaron Sloman, David Owen, Geoffrey E. Hinton, Frank Birch, Frank O'Gorman: Representation and Control in Vision. AISB/GI (ECAI) 1978: 309-314
	1976
1		Geoffrey E. Hinton: Using Relaxation to find a Puppet. AISB (ECAI) 1976: 148-157

Coauthor Index

1	Alex Acero (Alejandro Acero)	[135]
2	David H. Ackley	[6]
3	Suzanna Becker	[27] [30]
4	Yoshua Bengio	[120]
5	Frank Birch	[2]
6	Andrew D. Brown	[56] [70]
7	Drew van Camp	[33]
8	Jen-Tzung Chien	[153]
9	James Cook	[96]
10	George E. Dahl	[131] [147] [154]
11	Peter Dayan	[29] [37] [38] [39] [42] [46]
12	Li Deng	[135]
13	Gregory Dudek	[45]
14	Scott E. Fahlman	[5] [10]
15	Sidney Fels (S. Sidney Fels)	[24] [35] [41] [50]
16	David J. Fleet	[139]
17	Brendan J. Frey	[39] [44] [48] [54]
18	Conrad C. Galland	[14] [16]
19	Zoubin Ghahramani	[49] [53] [55] [57] [58] [59]
20	Jacob Goldberger	[85]
21	Radek Grzeszczuk	[51] [52]
22	Nicolas Heess	[124]
23	Navdeep Jaitly	[145]
24	Michael I. Jordan	[36]
25	Alex Krizhevsky	[128] [148] [149]
26	Kevin J. Lang	[7] [18] [19]
27	Hugo Larochelle	[134] [143] [156]
28	Yann LeCun	[14] [120]
29	Hector J. Levesque	[74]
30	Laurens van der Maaten	[152]
31	James Martens	[144]
32	Guy Mayraz	[60] [72]
33	James L. McClelland (Jay McClelland)	[12]
34	Drew V. McDermott	[9]
35	Roland Memisevic	[86] [88] [103] [126] [133] [151]
36	Tom M. Mitchell	[118]
37	Andriy Mnih	[82] [96] [101] [102] [109] [111] [113]
38	Volodymyr Mnih	[132] [138] [143] [150] [156]
39	Abdel-rahman Mohamed	[131] [135] [137] [147] [154]
40	Nelson Morgan	[153]
41	Michael C. Mozer (Michael Mozer)	[17]
42	Vinod Nair	[89] [108] [110] [119] [136]
43	Ryohei Nakano	[53] [57] [58]
44	Radford M. Neal	[38]
45	Steven J. Nowlan	[22] [25] [28]
46	Frank O'Gorman	[2]
47	Sageev Oore	[45] [73] [79]
48	Simon Osindero	[77] [80] [91] [92] [93] [100]
49	David Owen	[2]
50	Alberto Paccanaro	[63] [64] [66] [69]
51	Mark Palatucci	[118]
52	Michael Picheny (Michael A. Picheny)	[147]
53	Fiora Pirri	[74]
54	Marc Pollefeys	[133] [151]
55	Dean Pomerleau	[118]
56	Bhuvana Ramabhadran	[146] [147]
57	Marc'Aurelio Ranzato	[128] [131] [132] [140] [150]
58	Michael Revow	[26] [34] [37] [40] [43] [47]
59	Michal Rosen-Zvi	[87]
60	Sam T. Roweis	[68] [75] [85] [94] [141]
61	Shigeki Sagayama	[153]
62	Tara N. Sainath	[147]
63	Ruslan Salakhutdinov	[85] [98] [99] [101] [114] [115] [117] [120]
64	Brian Sallans	[62] [83]
65	Ruhi Sarikaya	[146]
66	Lawrence K. Saul	[68]
67	Tanya Schmah	[107] [127]
68	Terrence J. Sejnowski	[5] [6]
69	Michael L. Seltzer	[135]
70	Leonid Sigal	[139]
71	Aaron Sloman	[2]
72	Steven L. Small	[107] [127]
73	Stephen C. Strother	[107] [127]
74	Joshua Susskind	[110] [150] [151]
75	Ilya Sutskever	[96] [97] [104] [105] [106] [125] [144]
76	Graham W. Taylor	[94] [105] [116] [122] [123] [139] [141] [155]
77	Yee Whye Teh	[55] [61] [67] [80] [91] [93]
78	Demetri Terzopoulos	[51] [52] [73] [79]
79	Tijmen Tieleman	[121]
80	David S. Touretzky	[8] [13]
81	Nikolaus F. Troje	[123]
82	Naonori Ueda	[53] [57] [58]
83	Alexander H. Waibel (Alex Waibel)	[19]
84	Sida D. Wang	[148]
85	Max Welling	[76] [77] [78] [80] [81] [82] [84] [87] [92] [93]
86	Christopher K. I. Williams	[26] [34] [43] [47] [124]
87	Lei Xu	[36]
88	Grigori Yourganov	[127]
89	Dong Yu	[135] [153]
90	Kay Yu	[120]
91	Zhang Yuecheng	[111] [113]
92	Christopher Zach	[133]
93	Matthew D. Zeiler	[123]
94	Richard S. Zemel	[17] [23] [31] [32] [38] [76] [81] [84] [107] [127]

Colors in the list of coauthors

Last update Sat Jun 2 20:57:36 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page