BibSLEIGH — Yoshua

Travelled to:

1 × Canada
1 × China
1 × Finland
1 × France
1 × Ireland
1 × United Kingdom
5 × USA

Collaborated with:

A.C.Courville P.Vincent H.Larochelle X.Glorot Y.Dauphin S.Rifai I.J.Goodfellow J.Bergstra ∅ K.Cho S.Gouws G.Corrado R.Pascanu T.Mikolov A.Sordoni J.Nie N.Boulanger-Lewandowski A.Bordes J.Chung Ç.Gülçehre E.Laufer G.Alain J.Yosinski M.Chen K.Q.Weinberger F.Sha G.Mesnil J.Louradour R.Collobert J.Weston P.Manzagol D.Warde-Farley M.Mirza X.Muller D.Erhan Eric Thibodeau-Laufer Raul Chandias Ferrari L.Yao Olivier Delalleau P.Haffner L.Bottou P.G.Howard P.Y.Simard Y.LeCun K.Xu J.Ba R.Kiros R.Salakhutdinov R.S.Zemel

Talks about:

learn (5) deep (5) network (4) generat (4) scale (4) model (4) represent (3) neural (3) featur (3) encod (3)

Person: Yoshua Bengio

DBLP: Bengio:Yoshua

Contributed to:

2015

2014

2013

2012

2011

2009

2008

2007

1998

2013

Wrote 23 papers:

ICML-2015-ChungGCB #feedback #network: Gated Feedback Recurrent Neural Networks (JC, ÇG, KC, YB), pp. 2067–2075.
ICML-2015-GouwsBC #distributed #named #performance #word: BilBOWA: Fast Bilingual Distributed Representations without Word Alignments (SG, YB, GC), pp. 748–756.
ICML-2015-XuBKCCSZB #generative #image #visual notation: Show, Attend and Tell: Neural Image Caption Generation with Visual Attention (KX, JB, RK, KC, ACC, RS, RSZ, YB), pp. 2048–2057.
ICML-c2-2014-BengioLAY #generative #network #probability: Deep Generative Stochastic Networks Trainable by Backprop (YB, EL, GA, JY), pp. 226–234.
ICML-c2-2014-ChenWSB: Marginalized Denoising Auto-encoders for Nonlinear Representations (MC, KQW, FS, YB), pp. 1476–1484.
KDD-2014-Bengio #learning #scalability: Scaling up deep learning (YB), p. 1966.
ICML-c1-2013-BengioMDR: Better Mixing via Deep Representations (YB, GM, YD, SR), pp. 552–560.
ICML-c3-2013-GoodfellowWMCB #network: Maxout Networks (IJG, DWF, MM, ACC, YB), pp. 1319–1327.
ICML-c3-2013-PascanuMB #network #on the: On the difficulty of training recurrent neural networks (RP, TM, YB), pp. 1310–1318.
SIGIR-2013-SordoniNB #dependence #information retrieval #modelling #quantum: Modeling term dependencies with quantum language models for IR (AS, JYN, YB), pp. 653–662.
ICML-2012-Boulanger-LewandowskiBV #dependence #generative #modelling #music #sequence: Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription (NBL, YB, PV), p. 244.
ICML-2012-GoodfellowCB #learning #scalability: Large-Scale Feature Learning With Spike-and-Slab Sparse Coding (IJG, ACC, YB), p. 180.
ICML-2012-RifaiDVB #generative #process: A Generative Process for Contractive Auto-Encoders (SR, YD, PV, YB), p. 235.
ICML-2011-CourvilleBB #image #modelling: Unsupervised Models of Images by Spikeand-Slab RBMs (ACC, JB, YB), pp. 1145–1152.
ICML-2011-DauphinGB #learning #re-engineering #scalability: Large-Scale Learning of Embeddings with Reconstruction Sampling (YD, XG, YB), pp. 945–952.
ICML-2011-GlorotBB #adaptation #approach #classification #learning #scalability #sentiment: Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach (XG, AB, YB), pp. 513–520.
ICML-2011-RifaiVMGB #feature model: Contractive Auto-Encoders: Explicit Invariance During Feature Extraction (SR, PV, XM, XG, YB), pp. 833–840.
ICML-2009-BengioLCW #education #learning: Curriculum learning (YB, JL, RC, JW), pp. 41–48.
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.
ADL-1998-HaffnerBHSBC #documentation #image #quality: Browsing through High Quality Document Images with DjVu (PH, LB, PGH, PYS, YB, YL), pp. 309–318.
CIG-2013-Thibodeau-LauferFYDB #evaluation #game studies #policy #video: Stacked calibration of off-policy policy evaluation for video game matchmaking (ETL, RCF, LY, OD, YB), pp. 1–8.