James Bergstra

According to our database1, James Bergstra authored at least 21 papers between 2006 and 2019.

Collaborative distances:



In proceedings 
PhD thesis 


On csauthors.net:


Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Setting up a Reinforcement Learning Task with a Real-World Robot.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Benchmarking Reinforcement Learning Algorithms on Real-World Robots.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Challenges in representation learning: A report on three machine learning contests.
Neural Networks, 2015

The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions.
IEEE Trans. Pattern Anal. Mach. Intell., 2014

Nengo: a Python tool for building large-scale functional brain models.
Front. Neuroinform., 2014


Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures.
Proceedings of the 30th International Conference on Machine Learning, 2013

A Neural Model of Human Image Categorization.
Proceedings of the 35th Annual Meeting of the Cognitive Science Society, 2013

Unsupervised and Transfer Learning Challenge: a Deep Learning Approach.
Proceedings of the Unsupervised and Transfer Learning, 2012

Random Search for Hyper-Parameter Optimization.
J. Mach. Learn. Res., 2012

Suitability of V1 Energy Models for Object Classification.
Neural Computation, 2011

A Spike and Slab Restricted Boltzmann Machine.
Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Algorithms for Hyper-Parameter Optimization.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Unsupervised Models of Images by Spikeand-Slab RBMs.
Proceedings of the 28th International Conference on Machine Learning, 2011

Scalable Genre and Tag Prediction with Spectral Covariance.
Proceedings of the 11th International Society for Music Information Retrieval Conference, 2010

Slow, Decorrelated Features for Pretraining Complex Cell-like Networks.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Quadratic Features and Deep Architectures for Chunking.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, May 31, 2009

An empirical evaluation of deep architectures on problems with many factors of variation.
Proceedings of the Machine Learning, 2007

Aggregate features and ADABOOSTfor music classification.
Machine Learning, 2006

Predicting genre labels for artist using FreeDB.
Proceedings of the ISMIR 2006, 2006