| Natural language processing (almost) from scratch R Collobert, J Weston, L Bottou, M Karlen, K Kavukcuoglu, P Kuksa Journal of machine learning research 12 (ARTICLE), 2493− 2537, 2011 | 7034 | 2011 |
| A unified architecture for natural language processing: Deep neural networks with multitask learning R Collobert, J Weston Proceedings of the 25th international conference on Machine learning, 160-167, 2008 | 5262 | 2008 |
| Curriculum learning Y Bengio, J Louradour, R Collobert, J Weston Proceedings of the 26th annual international conference on machine learning …, 2009 | 2547 | 2009 |
| Torch7: A matlab-like environment for machine learning R Collobert, K Kavukcuoglu, C Farabet BigLearn, NIPS workshop, 2011 | 1645 | 2011 |
| SVMTorch: Support vector machines for large-scale regression problems R Collobert, S Bengio Journal of machine learning research 1 (Feb), 143-160, 2001 | 1138 | 2001 |
| Deep learning via semi-supervised embedding J Weston, F Ratle, H Mobahi, R Collobert Neural networks: Tricks of the trade, 639-655, 2012 | 959 | 2012 |
| Learning structured embeddings of knowledge bases A Bordes, J Weston, R Collobert, Y Bengio Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 2011 | 765 | 2011 |
| Recurrent convolutional neural networks for scene labeling P Pinheiro, R Collobert International conference on machine learning, 82-90, 2014 | 743 | 2014 |
| Learning to refine object segments PO Pinheiro, TY Lin, R Collobert, P Dollár ECCV, 2016 | 652 | 2016 |
| Learning to segment object candidates PO O Pinheiro, R Collobert, P Dollár Advances in neural information processing systems 28, 1990-1998, 2015 | 611 | 2015 |
| Combining active learning and semi-supervised learning using gaussian fields and harmonic functions X Zhu, J Lafferty, Z Ghahramani ICML 2003 workshop on the continuum from labeled to unlabeled data in …, 2003 | 561 | 2003 |
| Torch: a modular machine learning software library R Collobert, S Bengio, J Mariéthoz Idiap, 2002 | 546 | 2002 |
| Large scale transductive SVMs R Collobert, F Sinz, J Weston, L Bottou Journal of Machine Learning Research 7 (Aug), 1687-1712, 2006 | 524 | 2006 |
| A parallel mixture of SVMs for very large scale problems R Collobert, S Bengio, Y Bengio Neural computation 14 (5), 1105-1114, 2002 | 473 | 2002 |
| From image-level to pixel-level labeling with convolutional networks PO Pinheiro, R Collobert Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 457 | 2015 |
| Trading convexity for scalability R Collobert, F Sinz, J Weston, L Bottou Proceedings of the 23rd international conference on Machine learning, 201-208, 2006 | 373 | 2006 |
| Deep learning from temporal coherence in video H Mobahi, R Collobert, J Weston Proceedings of the 26th Annual International Conference on Machine Learning …, 2009 | 346 | 2009 |
| Video (language) modeling: a baseline for generative models of natural videos MA Ranzato, A Szlam, J Bruna, M Mathieu, R Collobert, S Chopra arXiv preprint arXiv:1412.6604, 2014 | 337 | 2014 |
| Links between perceptrons, MLPs and SVMs R Collobert, S Bengio Proceedings of the twenty-first international conference on Machine learning, 23, 2004 | 307 | 2004 |
| Word emdeddings through hellinger PCA R Lebret, R Collobert arXiv preprint arXiv:1312.5542, 2013 | 262 | 2013 |
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