| 2009 | ||
|---|---|---|
| 92 | 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 | |
| 91 | Kay Yu, Ruslan Salakhutdinov, Yann LeCun, Geoffrey E. Hinton, Yoshua Bengio: Workshop summary: Workshop on learning feature hierarchies. ICML 2009: 165 | |
| 90 | Yoshua Bengio, Jérôme Louradour, Ronan Collobert, Jason Weston: Curriculum learning. ICML 2009: 6 | |
| 89 | Yoshua Bengio: Learning Deep Architectures for AI. Foundations and Trends in Machine Learning 2(1): 1-127 (2009) | |
| 88 | 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 | Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pierre-Antoine Manzagol: Extracting and composing robust features with denoising autoencoders. ICML 2008: 1096-1103 | |
| 85 | Hugo Larochelle, Yoshua Bengio: Classification using discriminative restricted Boltzmann machines. ICML 2008: 536-543 | |
| 84 | 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 | Nicolas Le Roux, Yoshua Bengio: Representational Power of Restricted Boltzmann Machines and Deep Belief Networks. Neural Computation 20(6): 1631-1649 (2008) | |
| 82 | Yoshua Bengio: Neural net language models. Scholarpedia 3(1): 3881 (2008) | |
| 2007 | ||
| 81 | 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 | Nicolas Chapados, Yoshua Bengio: Augmented Functional Time Series Representation and Forecasting with Gaussian Processes. NIPS 2007 | |
| 79 | Nicolas Le Roux, Yoshua Bengio, Pascal Lamblin, Marc Joliveau, Balázs Kégl: Learning the 2-D Topology of Images. NIPS 2007 | |
| 78 | Nicolas Le Roux, Pierre-Antoine Manzagol, Yoshua Bengio: Topmoumoute Online Natural Gradient Algorithm. NIPS 2007 | |
| 77 | 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 | 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 | Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle: Greedy Layer-Wise Training of Deep Networks. NIPS 2006: 153-160 | |
| 74 | 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 | 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 | Yoshua Bengio, Nicolas Le Roux, Pascal Vincent, Olivier Delalleau, Patrice Marcotte: Convex Neural Networks. NIPS 2005 | |
| 70 | Yoshua Bengio, Hugo Larochelle, Pascal Vincent: Non-Local Manifold Parzen Windows. NIPS 2005 | |
| 69 | Yoshua Bengio, Olivier Delalleau, Nicolas Le Roux: The Curse of Highly Variable Functions for Local Kernel Machines. NIPS 2005 | |
| 2004 | ||
| 68 | Indrajit Bhattacharya, Lise Getoor, Yoshua Bengio: Unsupervised Sense Disambiguation Using Bilingual Probabilistic Models. ACL 2004: 287-294 | |
| 67 | François Rivest, Yoshua Bengio, John Kalaska: Brain Inspired Reinforcement Learning. NIPS 2004 | |
| 66 | Yoshua Bengio, Martin Monperrus: Non-Local Manifold Tangent Learning. NIPS 2004 | |
| 65 | Yves Grandvalet, Yoshua Bengio: Semi-supervised Learning by Entropy Minimization. NIPS 2004 | |
| 64 | 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 | 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 | Yoshua Bengio, Yves Grandvalet: No Unbiased Estimator of the Variance of K-Fold Cross-Validation. NIPS 2003 | |
| 61 | 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 | Ronan Collobert, Yoshua Bengio, Samy Bengio: Scaling Large Learning Problems with Hard Parallel Mixtures. IJPRAI 17(3): 349-365 (2003) | |
| 59 | Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Janvin: A Neural Probabilistic Language Model. Journal of Machine Learning Research 3: 1137-1155 (2003) | |
| 58 | Yoshua Bengio, Nicolas Chapados: Extensions to Metric-Based Model Selection. Journal of Machine Learning Research 3: 1209-1227 (2003) | |
| 57 | Claude Nadeau, Yoshua Bengio: Inference for the Generalization Error. Machine Learning 52(3): 239-281 (2003) | |
| 2002 | ||
| 56 | Pascal Vincent, Yoshua Bengio: Manifold Parzen Windows. NIPS 2002: 825-832 | |
| 55 | 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 | Ichiro Takeuchi, Yoshua Bengio, Takafumi Kanamori: Robust Regression with Asymmetric Heavy-Tail Noise Distributions. Neural Computation 14(10): 2469-2496 (2002) | |
| 50 | 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 | 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 | Ronan Collobert, Samy Bengio, Yoshua Bengio: A Parallel Mixture of SVMs for Very Large Scale Problems. NIPS 2001: 633-640 | |
| 47 | Pascal Vincent, Yoshua Bengio: K-Local Hyperplane and Convex Distance Nearest Neighbor Algorithms. NIPS 2001: 985-992 | |
| 46 | Narjès Boufaden, Guy Lapalme, Yoshua Bengio: Topic Segmentation : A First Stage to Dialog-Based Information Extraction. NLPRS 2001: 273-279 | |
| 2000 | ||
| 45 | Yoshua Bengio: Continuous Optimization of Hyper-Parameters. IJCNN (1) 2000: 305-310 | |
| 44 | Joumana Ghosn, Yoshua Bengio: Bias Learning, Knowledge Sharing. IJCNN (1) 2000: 9-14 | |
| 43 | Pascal Vincent, Yoshua Bengio: A Neural Support Vector Network Architecture with Adaptive Kernels. IJCNN (5) 2000: 187-192 | |
| 42 | 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 | Steven Pigeon, Yoshua Bengio: Binary Pseudowavelets and Applications to Bilevel Image Processing. Data Compression Conference 1999: 364-373 | |
| 36 | Claude Nadeau, Yoshua Bengio: Inference for the Generalization Error. NIPS 1999: 307-313 | |
| 35 | Yoshua Bengio, Samy Bengio: Modeling High-Dimensional Discrete Data with Multi-Layer Neural Networks. NIPS 1999: 400-406 | |
| 34 | 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 | Léon Bottou, Paul G. Howard, Yoshua Bengio: The Z-Coder Adaptive Binary Coder. Data Compression Conference 1998: 13-22 | |
| 30 | 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 | 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 | Yoshua Bengio: Using a Financial Training Criterion Rather than a Prediction Criterion. Int. J. Neural Syst. 8(4): 433-443 (1997) | |
| 1996 | ||
| 23 | Joumana Ghosn, Yoshua Bengio: Multi-Task Learning for Stock Selection. NIPS 1996: 946-952 | |
| 1995 | ||
| 22 | Yoshua Bengio, Francois Gingras: Recurrent Neural Networks for Missing or Asynchronous Data. NIPS 1995: 395-401 | |
| 21 | 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 | 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 | Yoshua Bengio, Paolo Frasconi: An Input Output HMM Architecture. NIPS 1994: 427-434 | |
| 16 | Yoshua Bengio, Paolo Frasconi: Diffusion of Credit in Markovian Models. NIPS 1994: 553-560 | |
| 15 | Léon Bottou, Yoshua Bengio: Convergence Properties of the K-Means Algorithms. NIPS 1994: 585-592 | |
| 1993 | ||
| 14 | Yoshua Bengio, Paolo Frasconi: Credit Assignment through Time: Alternatives to Backpropagation. NIPS 1993: 75-82 | |
| 13 | 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 | 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 | 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 | 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 | 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 | Yoshua Bengio, Renato de Mori, Régis Cardin: Speaker Independent Speech Recognition with Neural Networks and Speech Knowledge. NIPS 1989: 218-225 | |
| 4 | 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 | Yoshua Bengio, Régis Cardin, Renato de Mori, Piero Cosi: Use of Multi-Layered Networks for Coding Speech with Phonetic Features. NIPS 1988: 224-231 | |