Keywords:
Publications of Ronan Collobert sorted by title
| 1 | 2 |
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| "The Sum of Its Parts": Joint Learning of Word and Phrase Representations with Autoencoders, and , Idiap-RR-21-2015 |
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A
| A Gentle Hessian for Efficient Gradient Descent, and , in: IEEE International Conference on Acoustic, Speech, and Signal Processing, ICASSP, 2004 |
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| A New Margin-Based Criterion for Efficient Gradient Descent, and , Idiap-RR-16-2003 |
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| A Parallel Mixture of SVMs for Very Large Scale Problems, , and , in: Neural Computation, 14(05), 2002 |
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| A Parallel Mixture of SVMs for Very Large Scale Problems, , and , in: Advances in Neural Information Processing Systems, NIPS 14, MIT Press, 2002 |
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| A Parallel Mixture of SVMs for Very Large Scale Problems, , and , Idiap-RR-12-2001 |
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| Analysis of CNN-based Speech Recognition System using Raw Speech as Input, , and , Idiap-RR-23-2015 |
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| Analysis of CNN-based Speech Recognition System using Raw Speech as Input, , and , in: Proceedings of Interspeech, ISCA, Dresden, pages 11-15, ISCA, 2015 |
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C
| Convolutional Neural Networks-based Continuous Speech Recognition using Raw Speech Signal, , and , Idiap-RR-18-2014 |
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| Convolutional Neural Networks-based Continuous Speech Recognition using Raw Speech Signal, , and , in: International Conference on Acoustics, Speech and Signal Procecssing, IEEE, South Brisbane, QLD, pages 4295 - 4299, IEEE, 2015 |
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D
| Deep Learning for Efficient Discriminative Parsing, , in: International Conference on Artificial Intelligence and Statistics, 2011 |
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| Deep Learning via Semi-Supervised Embedding, , , and , in: In Neural Networks: Tricks of the Trade, Springer, 2012 |
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| Deep Neural Networks for Syntactic Parsing of Morphologically Rich Languages, and , in: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016 |
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E
| End-to-End Acoustic Modeling using Convolutional Neural Networks for Automatic Speech Recognition, , and , Idiap-RR-18-2016 |
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| End-to-End Acoustic Modeling using Convolutional Neural Networks for HMM-based Automatic Speech Recognition, , and , in: Speech Communication, 108:15--32, 2019 |
[DOI] |
| End-to-end Phoneme Sequence Recognition using Convolutional Neural Networks, , and , Idiap-RR-40-2013 |
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| Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks, , and , Idiap-RR-13-2013 |
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| Estimating Phoneme Class Conditional Probabilities from Raw Speech Signal using Convolutional Neural Networks, , and , in: Proceedings of Interspeech, 2013 |
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F
| From Image-level to Pixel-level Labeling with Convolutional Networks, and , in: Computer Vision and Patter Recognition (CVPR), Boston, MA, pages 1713-1721, IEEE, 2015 |
[DOI] [URL] |
I
| Implementing Neural Networks Efficiently, , and , in: Neural Networks: Tricks of the Trade, Springer, 2012 |
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| Improving Object Classification using Pose Information, , , and , Idiap-RR-30-2012 |
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| Introduction to the Special Issue on Learning Semantics, , , , , and , in: Machine Learning, 2013 |
[DOI] |
| Is Deep Learning Really Necessary for Word Embeddings?, , and , Idiap-RR-44-2013 |
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J
| Joint Phoneme Segmentation Inference and Classification using CRFs, , and , in: Global Conference on Signal and Information Processing, Atlanta, GA, pages 587 - 591, IEEE, 2014 |
[DOI] |
| Joint RNN-Based Greedy Parsing and Word Composition, and , in: Proceedings of ICLR 2015, 2015 |
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L
| Large Scale Machine Learning, , Université de Paris VI, 2004 |
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| Large Scale Machine Learning, , Idiap-RR-42-2004 |
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| Learning linearly separable features for speech recognition using convolutional neural networks, , and , Idiap-RR-24-2015 |
[URL] |
| Learning Structured Embeddings of Knowledge Bases, , , and , in: Conference on Artificial Intelligence, 2011 |
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| Learning to Rank on Network Data, , and , in: Mining and Learning with Graphs, 2013 |
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| Learning to Refine Object Segments, , , and , in: Computer Vision - ECCV 2016, Amsterdam, pages 75-91, Springer, 2016 |
[DOI] [URL] |
| Learning to Segments Objects Candidates, , and , in: Advances in Neural Information Processing Systems, Montreal, Canada, pages 1990-1998, Curran Associates, Inc., 2015 |
[URL] |
| Links Between Perceptrons, MLPs and SVMs, and , in: International Conference on Machine Learning, ICML, 2004 |
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| Links between Perceptrons, MLPs and SVMs, and , Idiap-RR-06-2004 |
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N
| N-gram-Based Low-Dimensional Representation for Document Classification, and , in: International Conference on Learning Representations, 2015 |
[URL] |
| Natural Language Processing (Almost) from Scratch, , , , , and , in: Journal of Machine Learning Research, 12:2493-2537, 2011 |
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