Keywords:
- Auto-Encoders
- CD
- Cognition
- Computer Vision and Pattern Recognition
- Contrastive Divergence
- Convolutional Architectures
- cross validation
- curse of dimensionality
- decision trees
- Deep Learning
- Deep Networks
- Denoising Auto-Encoders.
- dimensionality reduction
- eigenfunctions learning
- Energy-based models
- error bars
- fast training
- generalization error inference
- importance sampling
- Isomap
- k-fold cross-validation
- kernel PCA
- language modeling
- Learning
- locally linear embedding
- model selection
- Monte Carlo methods
- Neural and Evolutionary Computing
- neural networks
- Neurons
- Nystrom formula
- parity function
- PCD
- probabilistic neural networks
- RBM
- Restricted Boltzmann Machine
- Restricted Boltzmann Machines
- simulated tempering
- spectral methods
- statistical comparison of algorithms
- tempered MCMC
- Transfer Learning
- unsupervised learning
- variance estimate
- Vision
Publications of Yoshua Bengio
| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-299 |
2012
| , , and , A Generative Process for Sampling Contractive Auto-Encoders, in: ICML'2012, Edinburgh, Scotland, U.K., 2012 |
| , Evolving Culture vs Local Minima, Université de Montréal, number ArXiv 1203.2990v1, 2012 |
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| , , and , Joint Learning of Words and Meaning Representations for Open-Text Semantic Parsing (2012), in: Proceedings of the 15th International Conference on Artificial Intelligence and Statistics (AISTATS) |
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| , , and , Learning Algorithms for the Classification Restricted Boltzmann Machine (2012), in: JMLR, 13(643-669) |
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| , and , On Training Deep Boltzmann Machines, Université de Montréal, number arXiv:1203.4416v1, 2012 |
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| and , Random Search for Hyper-Parameter Optimization (2012), in: Journal of Machine Learning Research, 13(281--305) |
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2011
| , , , and , A Common GPU n-Dimensional Array for Python and C, in: Big Learn workshop, NIPS'11, 2011 |
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| , and , A Spike and Slab RBM Approach to Modeling Natural Images, The Learning Workshop, Fort Lauderdale, FL., 2011 |
| , and , A Spike and Slab Restricted Boltzmann Machine, in: Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011 |
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| and , Adaptive Drift-Diffusion Process to Learn Time Intervals, University of Montreal, 2011 |
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| , , and , Adding noise to the input of a model trained with a regularized objective, Université de Montréal, number 1359, 2011 |
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| , , and , Algorithms for Hyper-Parameter Optimization, in: NIPS'2011, 2011 |
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| , , , , , and , Contextual tag inference (2011), in: ACM Transactions on Multimedia Computing, Communications and Applications, 7S(32:1–32:18) |
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| , , , and , Contracting Auto-Encoders: Explicit invariance during feature extraction, in: Proceedings of the Twenty-eight International Conference on Machine Learning (ICML'11), 2011 |
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| , , , , , , , , , , , , , , , and , Deep Learners Benefit More from Out-of-Distribution Examples, in: JMLR W\&CP: Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2011), Fort Lauderdale, FL, USA, 2011 |
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| , Deep Learning of Representations for Unsupervised and Transfer Learning, in: JMLR W\&CP: Proc. Unsupervised and Transfer Learning challenge and workshop, 2011 |
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| , and , Deep Sparse Rectifier Neural Networks, in: JMLR W\&CP: Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2011), 2011 |
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| , , , and , Detonation Classification from Acoustic Signature with the Restricted Boltzmann Machine (2011), in: Computational Intelligence |
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| , and , Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach, in: Proceedings of the Twenty-eight International Conference on Machine Learning (ICML'11), 2011 |
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| , , , , , and , Higher Order Contractive Auto-Encoder, in: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2011 |
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| , and , Improving first and second-order methods by modeling uncertainty, in: Optimization for Machine Learning, MIT Press, 2011 |
| , and , Large-Scale Learning of Embeddings with Reconstruction Sampling, in: Proceedings of the Twenty-eighth International Conference on Machine Learning (ICML'11), 2011 |
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| , , , , and , Learning invariant features through local space contraction, Université de Montréal - DIRO - LISA, number 1360, 2011 |
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| , , and , Learning Structured Embeddings of Knowledge Bases, in: AAAI 2011, 2011 |
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| and , On the Expressive Power of Deep Architectures, in: Proceedings of the 22nd International Conference on Algorithmic Learning Theory, 2011 |
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| 1-25 | 26-50 | 51-75 | 76-100 | 101-125 | 126-150 | 151-175 | 176-200 | 201-225 | 226-250 | 251-275 | 276-299 |
