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Bengio, Y.
Bengio, Yoshua,
Creation class: 
Language material
Creation role: 
Related names: 
Chapados, Nicolas (1972-)
Delalleau, Olivier
Dugas, Charles (1972-)
Grandvalet, Yves
Lauzon, Vincent-Philippe (1973-)
Le Roux, Nicolas
McGill University
Nadeau, Claude
Paiement, Jean-François
Vincent, Pascal
Adaptive importance sampling to accelerate training of a neural probabilistic language model.
Bias learning, knowledge sharing
Collaborative Filtering on a Family of Biological Targets
Comment améliorer la capacité de généralisation des algorithmes d'apprentissage pour la prise de décisions financières
Connectionist models applied to automatic speech recognition
Continuous optimization of hyper-parameters
Cost functions and model combination for VaR-based asset allocation using neural networks.
Efficient non-parametric function induction in semi-supervised learning
Estimation de densité conditionnelle lorsque l'hypothèse de normalité est insatisfaisante
Étude du biais dans le prix des options
Experiments on the application of IOHMMs to model financial returns series
Forecasting non-stationary volatility with hyper-parameters
Global optimization of a neural network-hidden Markov model hybrid.
Inference for the generalization error.
Input decay : simple and effective soft variable selection
Input-output HMMs for sequence processing
Justifying and Generalizing Contrastive Divergence
Kernel matching pursuit
Learning eigenfunctions links spectral embedding and kernel PCA.
Learning from partial labels with minimum entropy
Learning long-term dependencies with gradient descent is difficult.
Locally linear embedding for dimensionality reduction in QSAR.
Locally weighted full covariance Gaussian density estimation
Manifold Parzen windows
Memory-efficient adaptive Huffman coding algorithm for very large sets of symbols
Metric-based model selection for time-series forecasting
Model selection for small sample regression
Module for constructing trainable modular network in which each module inputs and outputs data structured as a graph
Multi-task learning for option pricing
Neural networks for speech and sequence recognition, c1996:
neural probabilistic language model., A
Neural Support Vector Network architecture with adaptive kernels
No unbiased estimator of the variance of K-fold cross-validation
Nonlocal Estimation of Manifold Structure
On out-of-sample statistics for time-series
On the challenge of learning complex functions.
parallel mixture of SVMs for very large scale problems., A
Probabilistic neural network models for sequential data
Programmable execution of multi-layered networks for automatic speech recognition
Quickly Generating Representative Samples from an RBM-Derived Process
Régularisation du prix des options : Stacking
Representational Power of Restricted Boltzmann Machines and Deep Belief Networks
Scaling large learning problems with hard parallel mixtures.
Spectral clustering and kernel PCA are learning eigenfunctions
Spectral dimensionality reduction
Stochastic gradient descent on a portfolio management training criterion using the IPA gradient estimator
Taking on the curse of dimensionality in joint distributions using neural networks
Use of genetic programming for the search of a new learning rule for neural networks
Using a financial training criterion rather than a prediction criterion.
Valorisation d'options par optimisation du Sharpe Ratio
Z-coder: a fast adaptive binary arithmetic coder
Contributed to or performed: 
Includes abstract in English and French
Thesis (M. Sc.)--McGill University, 1988