Travelled to:
1 × Canada
1 × Israel
1 × United Kingdom
5 × USA
Collaborated with:
R.Salakhutdinov Y.Tang A.Mnih I.Sutskever J.Martens V.Mnih V.Nair G.W.Taylor T.Tieleman A.Paccanaro S.Fels G.E.Dahl
Talks about:
boltzmann (3) restrict (3) machin (3) model (3) learn (3) deep (3) network (2) linear (2) improv (2) factor (2)
Person: Geoffrey E. Hinton
DBLP: Hinton:Geoffrey_E=
Contributed to:
Wrote 13 papers:
- ICML-c3-2013-SutskeverMDH #learning #on the
- On the importance of initialization and momentum in deep learning (IS, JM, GED, GEH), pp. 1139–1147.
- ICML-c3-2013-TangSH
- Tensor Analyzers (YT, RS, GEH), pp. 163–171.
- ICML-2012-MnihH #image #learning #semistructured data
- Learning to Label Aerial Images from Noisy Data (VM, GEH), p. 31.
- ICML-2012-TangSH
- Deep Mixtures of Factor Analysers (YT, RS, GEH), p. 147.
- ICML-2012-TangSH12a #network
- Deep Lambertian Networks (YT, RS, GEH), p. 184.
- ICML-2011-SutskeverMH #generative #network
- Generating Text with Recurrent Neural Networks (IS, JM, GEH), pp. 1017–1024.
- ICML-2010-NairH #linear #strict
- Rectified Linear Units Improve Restricted Boltzmann Machines (VN, GEH), pp. 807–814.
- ICML-2009-TaylorH #modelling #strict
- Factored conditional restricted Boltzmann Machines for modeling motion style (GWT, GEH), pp. 1025–1032.
- ICML-2009-TielemanH #performance #persistent #using
- Using fast weights to improve persistent contrastive divergence (TT, GEH), pp. 1033–1040.
- ICML-2007-MnihH #modelling #statistics #visual notation
- Three new graphical models for statistical language modelling (AM, GEH), pp. 641–648.
- ICML-2007-SalakhutdinovMH #collaboration #strict
- Restricted Boltzmann machines for collaborative filtering (RS, AM, GEH), pp. 791–798.
- ICML-2000-PaccanaroH #concept #distributed #learning #linear
- Learning Distributed Representations by Mapping Concepts and Relations into a Linear Space (AP, GEH), pp. 711–718.
- CHI-1995-FelsH #adaptation #interface #named
- GloveTalkII: An Adaptive Gesture-to-Formant Interface (SF, GEH), pp. 456–463.