BibSLEIGH corpus
BibSLEIGH tags
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BibSLEIGH people
Open Knowledge
XHTML 1.0 W3C Rec
CSS 2.1 W3C CanRec
email twitter
Travelled to:
1 × China
1 × Finland
1 × France
1 × Sweden
1 × United Kingdom
4 × USA
Collaborated with:
Y.Bengio R.S.Zemel I.Murray B.Uria M.Havaei P.Jodoin L.Charlin M.Volkovs G.E.Dahl R.P.Adams M.Germain K.Gregor A.Lacoste M.Marchand F.Laviolette P.Vincent P.Manzagol L.Bazzani N.d.Freitas V.Murino J.Ting D.Erhan A.C.Courville J.Bergstra
Talks about:
learn (3) deep (3) boltzmann (2) autoencod (2) restrict (2) classif (2) machin (2) estim (2) brain (2) architectur (1)

Person: Hugo Larochelle

DBLP DBLP: Larochelle:Hugo

Contributed to:

ICML 20152015
ICML c1 20142014
ICPR 20142014
KDD 20142014
CIKM 20122012
ICML 20122012
ICML 20112011
ICML 20082008
ICML 20072007

Wrote 11 papers:

ICML-2015-GermainGML #estimation #named
MADE: Masked Autoencoder for Distribution Estimation (MG, KG, IM, HL), pp. 881–889.
ICML-c1-2014-LacosteMLL #learning
Agnostic Bayesian Learning of Ensembles (AL, MM, FL, HL), pp. 611–619.
A Deep and Tractable Density Estimator (BU, IM, HL), pp. 467–475.
ICPR-2014-HavaeiJL #classification #interactive #performance #segmentation
Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification (MH, PMJ, HL), pp. 556–561.
KDD-2014-CharlinZL #collaboration #library
Leveraging user libraries to bootstrap collaborative filtering (LC, RSZ, HL), pp. 173–182.
CIKM-2012-VolkovsLZ #learning #rank
Learning to rank by aggregating expert preferences (MV, HL, RSZ), pp. 843–851.
ICML-2012-DahlAL #strict #word
Training Restricted Boltzmann Machines on Word Observations (GED, RPA, HL), p. 152.
ICML-2011-BazzaniFLMT #learning #network #policy #recognition #video
Learning attentional policies for tracking and recognition in video with deep networks (LB, NdF, HL, VM, JAT), pp. 937–944.
ICML-2008-LarochelleB #classification #strict #using
Classification using discriminative restricted Boltzmann machines (HL, YB), pp. 536–543.
ICML-2008-VincentLBM #robust
Extracting and composing robust features with denoising autoencoders (PV, HL, YB, PAM), pp. 1096–1103.
ICML-2007-LarochelleECBB #architecture #empirical #evaluation #problem
An empirical evaluation of deep architectures on problems with many factors of variation (HL, DE, ACC, JB, YB), pp. 473–480.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
Hosted as a part of SLEBOK on GitHub.