| * | 2009 |
|---|
| 91 | | Daphne Koller,
Dale Schuurmans,
Yoshua Bengio,
Léon Bottou:
Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008
MIT Press 2009 |
| 90 | EE | Kay Yu,
Ruslan Salakhutdinov,
Yann LeCun,
Geoffrey E. Hinton,
Yoshua Bengio:
Workshop summary: Workshop on learning feature hierarchies.
ICML 2009: 165 |
| 89 | EE | Yoshua Bengio,
Jérôme Louradour,
Ronan Collobert,
Jason Weston:
Curriculum learning.
ICML 2009: 6 |
| 88 | EE | Yoshua Bengio,
Olivier Delalleau:
Justifying and Generalizing Contrastive Divergence.
Neural Computation 21(6): 1601-1621 (2009) |
| 2008 |
|---|
| 87 | | Hugo Larochelle,
Dumitru Erhan,
Yoshua Bengio:
Zero-data Learning of New Tasks.
AAAI 2008: 646-651 |
| 86 | EE | Pascal Vincent,
Hugo Larochelle,
Yoshua Bengio,
Pierre-Antoine Manzagol:
Extracting and composing robust features with denoising autoencoders.
ICML 2008: 1096-1103 |
| 85 | EE | Hugo Larochelle,
Yoshua Bengio:
Classification using discriminative restricted Boltzmann machines.
ICML 2008: 536-543 |
| 84 | EE | Yoshua Bengio,
Jean-Sébastien Senecal:
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model.
IEEE Transactions on Neural Networks 19(4): 713-722 (2008) |
| 83 | EE | Nicolas Le Roux,
Yoshua Bengio:
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks.
Neural Computation 20(6): 1631-1649 (2008) |
| 82 | EE | Yoshua Bengio:
Neural net language models.
Scholarpedia 3(1): 3881 (2008) |
| 2007 |
|---|
| 81 | EE | Hugo Larochelle,
Dumitru Erhan,
Aaron C. Courville,
James Bergstra,
Yoshua Bengio:
An empirical evaluation of deep architectures on problems with many factors of variation.
ICML 2007: 473-480 |
| 80 | EE | Nicolas Chapados,
Yoshua Bengio:
Augmented Functional Time Series Representation and Forecasting with Gaussian Processes.
NIPS 2007 |
| 79 | EE | Nicolas Le Roux,
Yoshua Bengio,
Pascal Lamblin,
Marc Joliveau,
Balázs Kégl:
Learning the 2-D Topology of Images.
NIPS 2007 |
| 78 | EE | Nicolas Le Roux,
Pierre-Antoine Manzagol,
Yoshua Bengio:
Topmoumoute Online Natural Gradient Algorithm.
NIPS 2007 |
| 77 | EE | Nicolas Chapados,
Yoshua Bengio:
Noisy K Best-Paths for Approximate Dynamic Programming with Application to Portfolio Optimization.
JCP 2(1): 12-19 (2007) |
| 2006 |
|---|
| 76 | EE | Nicolas Chapados,
Yoshua Bengio:
The K Best-Paths Approach to Approximate Dynamic Programming with Application to Portfolio Optimization.
Canadian Conference on AI 2006: 491-502 |
| 75 | EE | Yoshua Bengio,
Pascal Lamblin,
Dan Popovici,
Hugo Larochelle:
Greedy Layer-Wise Training of Deep Networks.
NIPS 2006: 153-160 |
| 74 | EE | Dumitru Erhan,
Pierre-Jean L'Heureux,
Shi Yi Yue,
Yoshua Bengio:
Collaborative Filtering on a Family of Biological Targets.
Journal of Chemical Information and Modeling 46(2): 626-635 (2006) |
| 73 | EE | Yoshua Bengio,
Martin Monperrus,
Hugo Larochelle:
Nonlocal Estimation of Manifold Structure.
Neural Computation 18(10): 2509-2528 (2006) |
| 2005 |
|---|
| 72 | | Yves Grandvalet,
Yoshua Bengio:
Semi-supervised Learning by Entropy Minimization.
CAP 2005: 281-296 |
| 71 | EE | Yoshua Bengio,
Nicolas Le Roux,
Pascal Vincent,
Olivier Delalleau,
Patrice Marcotte:
Convex Neural Networks.
NIPS 2005 |
| 70 | EE | Yoshua Bengio,
Hugo Larochelle,
Pascal Vincent:
Non-Local Manifold Parzen Windows.
NIPS 2005 |
| 69 | EE | Yoshua Bengio,
Olivier Delalleau,
Nicolas Le Roux:
The Curse of Highly Variable Functions for Local Kernel Machines.
NIPS 2005 |
| 2004 |
|---|
| 68 | EE | Indrajit Bhattacharya,
Lise Getoor,
Yoshua Bengio:
Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models.
ACL 2004: 287-294 |
| 67 | EE | François Rivest,
Yoshua Bengio,
John Kalaska:
Brain Inspired Reinforcement Learning.
NIPS 2004 |
| 66 | EE | Yoshua Bengio,
Martin Monperrus:
Non-Local Manifold Tangent Learning.
NIPS 2004 |
| 65 | EE | Yves Grandvalet,
Yoshua Bengio:
Semi-supervised Learning by Entropy Minimization.
NIPS 2004 |
| 64 | EE | Yoshua Bengio,
Yves Grandvalet:
No Unbiased Estimator of the Variance of K-Fold Cross-Validation.
Journal of Machine Learning Research 5: 1089-1105 (2004) |
| 63 | EE | Yoshua Bengio,
Olivier Delalleau,
Nicolas Le Roux,
Jean-François Paiement,
Pascal Vincent,
Marie Ouimet:
Learning Eigenfunctions Links Spectral Embedding and Kernel PCA.
Neural Computation 16(10): 2197-2219 (2004) |
| 2003 |
|---|
| 62 | EE | Yoshua Bengio,
Yves Grandvalet:
No Unbiased Estimator of the Variance of K-Fold Cross-Validation.
NIPS 2003 |
| 61 | EE | Yoshua Bengio,
Jean-François Paiement,
Pascal Vincent,
Olivier Delalleau,
Nicolas Le Roux,
Marie Ouimet:
Out-of-Sample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering.
NIPS 2003 |
| 60 | EE | Ronan Collobert,
Yoshua Bengio,
Samy Bengio:
Scaling Large Learning Problems with Hard Parallel Mixtures.
IJPRAI 17(3): 349-365 (2003) |
| 59 | EE | Yoshua Bengio,
Réjean Ducharme,
Pascal Vincent,
Christian Janvin:
A Neural Probabilistic Language Model.
Journal of Machine Learning Research 3: 1137-1155 (2003) |
| 58 | EE | Yoshua Bengio,
Nicolas Chapados:
Extensions to Metric-Based Model Selection.
Journal of Machine Learning Research 3: 1209-1227 (2003) |
| 57 | EE | Claude Nadeau,
Yoshua Bengio:
Inference for the Generalization Error.
Machine Learning 52(3): 239-281 (2003) |
| 2002 |
|---|
| 56 | EE | Pascal Vincent,
Yoshua Bengio:
Manifold Parzen Windows.
NIPS 2002: 825-832 |
| 55 | EE | Ronan Collobert,
Yoshua Bengio,
Samy Bengio:
Scaling Large Learning Problems with Hard Parallel Mixtures.
SVM 2002: 8-23 |
| 54 | | Pascal Vincent,
Yoshua Bengio:
Kernel Matching Pursuit.
Machine Learning 48(1-3): 165-187 (2002) |
| 53 | | Yoshua Bengio,
Dale Schuurmans:
Guest Introduction: Special Issue on New Methods for Model Selection and Model Combination.
Machine Learning 48(1-3): 5-7 (2002) |
| 52 | | Olivier Chapelle,
Vladimir Vapnik,
Yoshua Bengio:
Model Selection for Small Sample Regression.
Machine Learning 48(1-3): 9-23 (2002) |
| 51 | EE | Ichiro Takeuchi,
Yoshua Bengio,
Takafumi Kanamori:
Robust Regression with Asymmetric Heavy-Tail Noise Distributions.
Neural Computation 14(10): 2469-2496 (2002) |
| 50 | EE | Ronan Collobert,
Samy Bengio,
Yoshua Bengio:
A Parallel Mixture of SVMs for Very Large Scale Problems.
Neural Computation 14(5): 1105-1114 (2002) |
| 2001 |
|---|
| 49 | EE | Nicolas Chapados,
Yoshua Bengio,
Pascal Vincent,
Joumana Ghosn,
Charles Dugas,
Ichiro Takeuchi,
Linyan Meng:
Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference.
NIPS 2001: 1369-1376 |
| 48 | EE | Ronan Collobert,
Samy Bengio,
Yoshua Bengio:
A Parallel Mixture of SVMs for Very Large Scale Problems.
NIPS 2001: 633-640 |
| 47 | EE | Pascal Vincent,
Yoshua Bengio:
K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms.
NIPS 2001: 985-992 |
| 46 | EE | Narjès Boufaden,
Guy Lapalme,
Yoshua Bengio:
Topic Segmentation : A First Stage to Dialog-Based Information Extraction.
NLPRS 2001: 273-279 |
| 2000 |
|---|
| 45 | EE | Yoshua Bengio:
Continuous Optimization of Hyper-Parameters.
IJCNN (1) 2000: 305-310 |
| 44 | EE | Joumana Ghosn,
Yoshua Bengio:
Bias Learning, Knowledge Sharing.
IJCNN (1) 2000: 9-14 |
| 43 | EE | Pascal Vincent,
Yoshua Bengio:
A Neural Support Vector Network Architecture with Adaptive Kernels.
IJCNN (5) 2000: 187-192 |
| 42 | EE | Yoshua Bengio:
Probabilistic Neural Network Models for Sequential Data.
IJCNN (5) 2000: 79-84 |
| 41 | | Charles Dugas,
Yoshua Bengio,
François Bélisle,
Claude Nadeau,
René Garcia:
Incorporating Second-Order Functional Knowledge for Better Option Pricing.
NIPS 2000: 472-478 |
| 40 | | Yoshua Bengio,
Réjean Ducharme,
Pascal Vincent:
A Neural Probabilistic Language Model.
NIPS 2000: 932-938 |
| 39 | | Holger Schwenk,
Yoshua Bengio:
Boosting Neural Networks.
Neural Computation 12(8): 1869-1887 (2000) |
| 38 | | Yoshua Bengio:
Gradient-Based Optimization of Hyperparameters.
Neural Computation 12(8): 1889-1900 (2000) |
| 1999 |
|---|
| 37 | EE | Steven Pigeon,
Yoshua Bengio:
Binary Pseudowavelets and Applications to Bilevel Image Processing.
Data Compression Conference 1999: 364-373 |
| 36 | EE | Claude Nadeau,
Yoshua Bengio:
Inference for the Generalization Error.
NIPS 1999: 307-313 |
| 35 | EE | Yoshua Bengio,
Samy Bengio:
Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks.
NIPS 1999: 400-406 |
| 34 | EE | Yann LeCun,
Patrick Haffner,
Léon Bottou,
Yoshua Bengio:
Object Recognition with Gradient-Based Learning.
Shape, Contour and Grouping in Computer Vision 1999: 319- |
| 33 | | Samy Bengio,
Yoshua Bengio,
Jacques Robert,
Gilles Bélanger:
Stochastic Learning of Strategic Equilibria for Auctions.
Neural Computation 11(5): 1199-1209 (1999) |
| 1998 |
|---|
| 32 | | Patrick Haffner,
Léon Bottou,
Paul G. Howard,
Patrice Simard,
Yoshua Bengio,
Yann LeCun:
Browsing through High Quality Document Images with DjVu.
ADL 1998: 309-318 |
| 31 | EE | Léon Bottou,
Paul G. Howard,
Yoshua Bengio:
The Z-Coder Adaptive Binary Coder.
Data Compression Conference 1998: 13-22 |
| 30 | EE | Steven Pigeon,
Yoshua Bengio:
A Memory-Efficient Adaptive Huffman Coding Algorthm for Very Large Sets of Symbols.
Data Compression Conference 1998: 568 |
| 29 | | Yoshua Bengio,
Francois Gingras,
Bernard Goulard,
Jean-Marc Lina,
Keith Scott:
Gaussian Mixture Densities for Classification of Nuclear Power Plant Data.
Computers and Artificial Intelligence 17(2-3): (1998) |
| 1997 |
|---|
| 28 | EE | Léon Bottou,
Yoshua Bengio,
Yann LeCun:
Global Training of Document Processing Systems Using Graph Transformer Networks.
CVPR 1997: 489-494 |
| 27 | | Holger Schwenk,
Yoshua Bengio:
AdaBoosting Neural Networks: Application to on-line Character Recognition.
ICANN 1997: 967-972 |
| 26 | | Yoshua Bengio,
Samy Bengio,
Jean-Franc Isabelle,
Yoram Singer:
Shared Context Probabilistic Transducers.
NIPS 1997 |
| 25 | | Holger Schwenk,
Yoshua Bengio:
Training Methods for Adaptive Boosting of Neural Networks.
NIPS 1997 |
| 24 | EE | Yoshua Bengio:
Using a Financial Training Criterion Rather than a Prediction Criterion.
Int. J. Neural Syst. 8(4): 433-443 (1997) |
| 1996 |
|---|
| 23 | EE | Joumana Ghosn,
Yoshua Bengio:
Multi-Task Learning for Stock Selection.
NIPS 1996: 946-952 |
| 1995 |
|---|
| 22 | EE | Yoshua Bengio,
Francois Gingras:
Recurrent Neural Networks for Missing or Asynchronous Data.
NIPS 1995: 395-401 |
| 21 | EE | Salah El Hihi,
Yoshua Bengio:
Hierarchical Recurrent Neural Networks for Long-Term Dependencies.
NIPS 1995: 493-499 |
| 20 | | Yoshua Bengio,
Paolo Frasconi:
Diffusion of Context and Credit Information in Markovian Models.
J. Artif. Intell. Res. (JAIR) 3: 249-270 (1995) |
| 19 | EE | Yoshua Bengio,
Yann LeCun,
Craig R. Nohl,
Christopher J. C. Burges:
LeRec: a NN/HMM hybrid for on-line handwriting recognition.
Neural Computation 7(6): 1289-1303 (1995) |
| 1994 |
|---|
| 18 | | Samy Bengio,
Yoshua Bengio,
Jocelyn Cloutier:
Use of Genetic Programming for the Search of a New Learning Rule for Neural Networks.
International Conference on Evolutionary Computation 1994: 324-327 |
| 17 | EE | Yoshua Bengio,
Paolo Frasconi:
An Input Output HMM Architecture.
NIPS 1994: 427-434 |
| 16 | EE | Yoshua Bengio,
Paolo Frasconi:
Diffusion of Credit in Markovian Models.
NIPS 1994: 553-560 |
| 15 | EE | Léon Bottou,
Yoshua Bengio:
Convergence Properties of the K-Means Algorithms.
NIPS 1994: 585-592 |
| 1993 |
|---|
| 14 | EE | Yoshua Bengio,
Paolo Frasconi:
Credit Assignment through Time: Alternatives to Backpropagation.
NIPS 1993: 75-82 |
| 13 | EE | Yoshua Bengio,
Yann LeCun,
Donnie Henderson:
Globally Trained Handwritten Word Recognizer Using Spatial Representation, Convolutional Neural Networks, and Hidden Markov Models.
NIPS 1993: 937-944 |
| 12 | | Yoshua Bengio:
A Connectionist Approach to Speech Recognition.
IJPRAI 7(4): 647-667 (1993) |
| 1992 |
|---|
| 11 | EE | Yoshua Bengio,
Renato de Mori,
Marco Gori:
Learning the dynamic nature of speech with back-propagation for sequences.
Pattern Recognition Letters 13(5): 375-385 (1992) |
| 10 | EE | Yoshua Bengio,
Renato de Mori,
Giovanni Flammia,
Ralf Kompe:
Phonetically motivated acoustic parameters for continuous speech recognition using artificial neural networks.
Speech Communication 11(2-3): 261-271 (1992) |
| 1991 |
|---|
| 9 | EE | Yoshua Bengio,
Renato de Mori,
Giovanni Flammia,
Ralf Kompe:
Neural Network - Gaussian Mixture Hybrid for Speech Recognition or Density Estimation.
NIPS 1991: 175-182 |
| 1990 |
|---|
| 8 | | Yoshua Bengio,
Yannick Pouliot:
Efficient recognition of immunoglobulin domains from amino acid sequences using a neural network.
Computer Applications in the Biosciences 6(4): 319-324 (1990) |
| 7 | EE | Piero Cosi,
Yoshua Bengio,
Renato de Mori:
Phonetically-based multi-layered neural networks for vowel classification.
Speech Communication 9(1): 15-29 (1990) |
| 1989 |
|---|
| 6 | | Renato de Mori,
Yoshua Bengio,
Piero Cosi:
On the Generalization Capability of Multi-Layered Networks in the Extraction of Speech Properties.
IJCAI 1989: 1531-1536 |
| 5 | EE | Yoshua Bengio,
Renato de Mori,
Régis Cardin:
Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge.
NIPS 1989: 218-225 |
| 4 | EE | Yoshua Bengio,
Samy Bengio,
Yannick Pouliot,
Patrick Agin:
A Neural Network to Detect Homologies in Proteins.
NIPS 1989: 423-430 |
| 3 | | Yoshua Bengio,
Régis Cardin,
Renato de Mori,
Ettore Merlo:
Programmable Execution of Multi-Layered Networks for Automatic Speech Recognition.
Commun. ACM 32(2): 195-199 (1989) |
| 1988 |
|---|
| 2 | | Renato de Mori,
Yoshua Bengio,
Régis Cardin:
Data-Driven Execution of Multi-Layered Networks for Automatic Speech Recognition.
AAAI 1988: 734-738 |
| 1 | EE | Yoshua Bengio,
Régis Cardin,
Renato de Mori,
Piero Cosi:
Use of Multi-Layered Networks for Coding Speech with Phonetic Features.
NIPS 1988: 224-231 |
