2012

• J. Bergstra and Y. Bengio (2012).
  Random Search for Hyper-Parameter Optimization.
  Journal of Machine Learning Research 13:281–305.
  [pdf]
  
• J. Bergstra, N. Pinto and D. D. Cox (2012).
  Machine Learning for Predictive Auto-Tuning with Boosted Regression Trees.
  Proc. Innovative Parallel Computing (INPAR12), Accepted.
  
  
  
  

2011

• J. Bergstra, R. Bardenet, Y. Bengio and B. Kégl (2011).
  Algorithms for Hyper-parameter Optimization.
  Proc. Neural Information Processing Systems 24 (NIPS2011), 2546–2554.
  [pdf]
  
• J. Bergstra, A. Courville and Y. Bengio (2011).
  The Statistical Inefficiency of Sparse Coding for Images (or, One Gabor to Rule them All).
  Technical report 1109.6638v2, arXiv.
  [pdf]
  
• J. Bergstra (2011).
  Incorporating Complex Cells into Neural Networks for Pattern Classification.
  Ph.D. Thesis, Université de Montréal.
  [pdf]
  
• A. Courville, J. Bergstra and Y. Bengio (2011).
  A Spike and Slab RBM Approach to Modeling Natural Images.
  The Learning Workshop, Fort Lauderdale, FL, USA.
  [pdf]
  
• J. Bergstra and Y. Bengio (2011).
  Random Search for Hyper-parameter Optimization.
  The Learning Workshop, Fort Lauderdale, FL, USA.
  [pdf]
  
• J. Bergstra, Y. Bengio and J. Louradour (2011).
  Suitability of V1 Energy Models for Object Classification.
  Neural Computation 23(3):774–790.
  [pdf]
  
• G. Mesnil, Y. Dauphin, X. Glorot, S. Rifai, Y. Bengio, I. Goodfellow, E. Lavoie, X. Muller, G. Desjardins, D. Warde-Farley, P. Vincent, A. Courville and J. Bergstra (2011).
  Unsupervised and Transfer Learning Challenge: a Deep Learning Approach.
  Workshop on Unsupervised and Transfer Learning, Bellevue, Washington, USA.
  [pdf]
  
• A. Courville, J. Bergstra and Y. Bengio (2011).
  Unsupervised Models of Images by Spike and Slab RBMs.
  Proc. 28th International Conference on Machine Learning (ICML-11), 1145–1152.
  [pdf] [bibtex]
  
• A. Courville, J. Bergstra and Y. Bengio (2011).
  The Spike and Slab Restricted Boltzmann Machine.
  Proc. Artificial Intelligence and Statistics (AISTATS), 233–241.
  [pdf]
  
• J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian and Y. Bengio (2011).
  Theano: Deep Learning on GPUs with Theano.
  (Under review)
  
  
  

2010

• A. Courville, J. Bergstra and Y. Bengio (2010).
  The Spike and Slab Restricted Boltzmann Machine.
  NIPS Deep Learning and Unsupervised Feature Learning Workshop, NIPS23.
  [pdf]
  
• J. Bergstra, M. Mandel and D. Eck (2010).
  Scalable Genre and Tag Prediction with Spectral Covariance.
  Proc. International Conference on Music Information Retrieval (ISMIR), 507–512.
  [pdf]
  
• J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian and Y. Bengio (2010).
  Theano: a CPU and GPU Math Expression Compiler.
  Proc. Python for Scientific Computing Conference (SciPy), 3–11.
  [slides] [video]
  
• J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, J. Turian, G. Desjardins, R. Pascanu, D. Erhan, O. Delalleau and Y. Bengio (2010).
  Deep Learning on GPUs with Theano.
  The Learning Workshop, Snowbird, Utah.
  [pdf]
  
• J. Bergstra, Y. Bengio, P. Lamblin, G. Desjardins and J. Louradour (2010).
  Image Classification with Complex Cell Neural Networks.
  Frontiers in Neuroscience Conference Abstract: Computational and Systems Neuroscience 2010.
  [link] [doi]
  
  
  

2009

• J. Bergstra and Y. Bengio (2009).
  Slow, Decorrelated Features for Pretraining Complex Cell-like Networks.
  Proc. Neural Information Processing Systems 22 (NIPS), 99–107.
  [pdf] [bibtex]
  
• J. Turian, J. Bergstra and Y. Bengio (2009).
  Quadratic Features and Deep Architectures for Chunking.
  Proc. North American Chapter of the Association for Computational Linguistics - Human Language Technologies (NAACL-HLT), 245–248.
  [pdf] [bibtex]
  
• J. Bergstra, G. Desjardins, P. Lamblin and Y. Bengio (2009).
  Quadratic Polynomials Learn Better Image Features.
  Technical report 1337, Département d’Informatique et de Recherche Opérationnelle, Université de Montréal.
  [pdf]
  
  
  

2008

• J. Bergstra, Y. Bengio and J. Louradour (2008).
  Image Classification using Higher-Order Neural Models.
  The Learning Workshop, Snowbird, Utah.
  [pdf]
  
  
  

2007

• H. Larochelle, D. Erhan, A. Courville, J. Bergstra and Y. Bengio (2007).
  An Empirical Evaluation of Deep Architectures on Problems with Many Factors of Variation.
  Proc. 24th International Conference on Machine Learning (ICML-07), 473–480.
  [pdf] [doi]
  
  
  

2006

• J. Bergstra, N. Casagrande, D. Eck and B. Kégl (2006).
  Aggregate Features and AdaBoost for Music Classification.
  Machine Learning 65:473–484.
  [pdf]
  
• J. Bergstra, A. Lacoste and D. Eck (2006).
  Predicting Genre Labels for Artists using FreeDB.
  Proc. International Conference on Music Information Retrieval (ISMIR), 85–88.
  [pdf]
  
• J. Bergstra (2006).
  Algorithms for Classifying Recorded Music by Genre.
  Masters Thesis, Université de Montréal.
  [pdf]
  
  
  

2005

• J. Bergstra, N. Casagrande and D. Eck (2005).
  Genre Classification: A Timbre- and Rhythm-Based Multiresolution Approach.
  MIREX Genre Classification Contest, London, England.
  [link]
  
• J. Bergstra, N. Casagrande and D. Eck (2005).
  Artist Recognition: A Timbre- and Rhythm-Based Multiresolution Approach.
  MIREX Artist Recognition Contest, London, England.
  [link]