| Random search for hyper-parameter optimization J Bergstra, Y Bengio Journal of Machine Learning Research 13, 281-305, 2012 | 10527 | 2012 |
| Algorithms for hyper-parameter optimization J Bergstra, R Bardenet, Y Bengio, B Kégl Advances in neural information processing systems 24, 2011 | 5617 | 2011 |
| Theano: a CPU and GPU math expression compiler J Bergstra, O Breuleux, F Bastien, P Lamblin, R Pascanu, G Desjardins, ... Proceedings of the Python for Scientific Computing Conference (SciPy), 2010 | 2805* | 2010 |
| Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures J Bergstra, D Yamins, DD Cox Proceedings of the 30th International Conference on Machine Learning (ICML …, 2013 | 2400 | 2013 |
| Theano: new features and speed improvements F Bastien, P Lamblin, R Pascanu, J Bergstra, I Goodfellow, A Bergeron, ... arXiv preprint arXiv:1211.5590, 2012 | 1675 | 2012 |
| Challenges in representation learning: A report on three machine learning contests IJ Goodfellow, D Erhan, PL Carrier, A Courville, M Mirza, B Hamner, ... Neural Information Processing: 20th International Conference, ICONIP 2013 …, 2013 | 1640 | 2013 |
| An empirical evaluation of deep architectures on problems with many factors of variation H Larochelle, D Erhan, A Courville, J Bergstra, Y Bengio Proceedings of the 24th international conference on Machine learning, 473-480, 2007 | 1338 | 2007 |
| Theano: A Python framework for fast computation of mathematical expressions R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, N Ballas, ... arXiv e-prints, arXiv: 1605.02688, 2016 | 913 | 2016 |
| Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms J Bergstra, D Yamins, DD Cox Proceedings of the 12th Python in Science Conference, 13 - 20, 2013 | 839 | 2013 |
| Nengo: a Python tool for building large-scale functional brain models T Bekolay, J Bergstra, E Hunsberger, T DeWolf, TC Stewart, ... Frontiers in neuroinformatics 7, 48, 2014 | 489 | 2014 |
| Towards an empirical foundation for assessing bayesian optimization of hyperparameters K Eggensperger, M Feurer, F Hutter, J Bergstra, J Snoek, H Hoos, ... NIPS workshop on Bayesian Optimization in Theory and Practice 10 (3), 2013 | 426 | 2013 |
| Aggregate features and ADABOOST for music classification J Bergstra, N Casagrande, D Erhan, D Eck, B Kégl Machine learning 65, 473-484, 2006 | 389 | 2006 |
| Hyperopt-sklearn: automatic hyperparameter configuration for scikit-learn B Komer, J Bergstra, C Eliasmith ICML workshop on AutoML 9, 50, 2014 | 364 | 2014 |
| Pylearn2: a machine learning research library IJ Goodfellow, D Warde-Farley, P Lamblin, V Dumoulin, M Mirza, ... arXiv preprint arXiv:1308.4214, 2013 | 361 | 2013 |
| Theano: Deep learning on gpus with python J Bergstra, F Bastien, O Breuleux, P Lamblin, R Pascanu, O Delalleau, ... NIPS 2011, BigLearning Workshop, Granada, Spain 3 (0), 2011 | 347 | 2011 |
| Unsupervised and transfer learning challenge: a deep learning approach G Mesnil, Y Dauphin, X Glorot, S Rifai, Y Bengio, I Goodfellow, E Lavoie, ... Proceedings of ICML Workshop on Unsupervised and Transfer Learning, 97-110, 2012 | 272 | 2012 |
| Theano: A Python framework for fast computation of mathematical expressions TTD Team, R Al-Rfou, G Alain, A Almahairi, C Angermueller, D Bahdanau, ... arXiv preprint arXiv:1605.02688, 2016 | 197 | 2016 |
| Benchmarking reinforcement learning algorithms on real-world robots AR Mahmood, D Korenkevych, G Vasan, W Ma, J Bergstra Conference on robot learning, 561-591, 2018 | 162 | 2018 |
| A spike and slab restricted Boltzmann machine A Courville, J Bergstra, Y Bengio Proceedings of the fourteenth international conference on artificial …, 2011 | 132 | 2011 |
| Unsupervised models of images by spike-and-slab RBMs A Courville, J Bergstra, Y Bengio ICML, 2011 | 98 | 2011 |
Yoshua BengioProfessor of computer science, University of Montreal, Mila, IVADO, CIFARVerified email at umontreal.ca
