James Bergstra

44 papers A* 3A 2B 1Misc 1Journal 21Unranked 13

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Offline-to-online Reinforcement Learning for Image-based Grasping with Scarce Demonstrations. CoRR Bryan Chan, Anson Leung, James Bergstra
2024	J	`jnl`	Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning. RLJ Gautham Vasan, Yan Wang, Fahim Shahriar, James Bergstra, Martin Jägersand, A. Rupam Mahmood
2024	J	`jnl`	Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning. CoRR Gautham Vasan, Yan Wang, Fahim Shahriar, James Bergstra, Martin Jägersand, A. Rupam Mahmood
2023	J	`jnl`	A Statistical Guarantee for Representation Transfer in Multitask Imitation Learning. CoRR Bryan Chan, Karime Pereida, James Bergstra
2020	J	`jnl`	Active Perception and Representation for Robotic Manipulation. CoRR Youssef Zaky, Gaurav Paruthi, Bryan P. Tripp, James Bergstra
2019	A*	`conf`	Autoregressive Policies for Continuous Control Deep Reinforcement Learning. IJCAI Dmytro Korenkevych, A. Rupam Mahmood, Gautham Vasan, James Bergstra
2019	J	`jnl`	Autoregressive Policies for Continuous Control Deep Reinforcement Learning. CoRR Dmytro Korenkevych, A. Rupam Mahmood, Gautham Vasan, James Bergstra
2019	—	`ch.`	Hyperopt-Sklearn. Automated Machine Learning Brent Komer, James Bergstra, Chris Eliasmith
2018	Misc	`conf`	Benchmarking Reinforcement Learning Algorithms on Real-World Robots. CoRL A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, James Bergstra
2018	J	`jnl`	Benchmarking Reinforcement Learning Algorithms on Real-World Robots. CoRR A. Rupam Mahmood, Dmytro Korenkevych, Gautham Vasan, William Ma, James Bergstra
2018	A	`conf`	Setting up a Reinforcement Learning Task with a Real-World Robot. IROS A. Rupam Mahmood, Dmytro Korenkevych, Brent J. Komer, James Bergstra
2018	J	`jnl`	Setting up a Reinforcement Learning Task with a Real-World Robot. CoRR A. Rupam Mahmood, Dmytro Korenkevych, Brent J. Komer, James Bergstra
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
2015	J	`jnl`	Challenges in representation learning: A report on three machine learning contests. Neural Networks Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2015	—	`ed.`	Proceedings of the 14th Python in Science Conference, SciPy 2015, Austin, Texas, USA, July 6-12, 2015 SciPy Kathryn D. Huff, James Bergstra
2014	—	`conf`	Hyperopt-Sklearn: Automatic Hyperparameter Configuration for Scikit-Learn. SciPy Brent Komer, James Bergstra, Chris Eliasmith
2014	—	`conf`	Preface. SciPy Andy Terrel, Jonathan Rocher, Stéfan van der Walt, James Bergstra
2014	—	`ed.`	Proceedings of the 13th Python in Science Conference, SciPy 2014, Austin, Texas, USA, July 6-12, 2014 SciPy Stéfan van der Walt, James Bergstra
2014	J	`jnl`	The Spike-and-Slab RBM and Extensions to Discrete and Sparse Data Distributions. IEEE Trans. Pattern Anal. Mach. Intell. Aaron C. Courville, Guillaume Desjardins, James Bergstra, Yoshua Bengio
2013	B	`conf`	A Neural Model of Human Image Categorization. CogSci Eric Hunsberger, Peter Blouw, James Bergstra, Chris Eliasmith
2013	—	`conf`	Challenges in Representation Learning: A Report on Three Machine Learning Contests. ICONIP (3) Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013	J	`jnl`	Challenges in Representation Learning: A report on three machine learning contests. CoRR Ian J. Goodfellow, Dumitru Erhan, Pierre Luc Carrier, Aaron C. Courville, Mehdi Mirza, Benjamin Hamner, William Cukierski, Yichuan Tang, David Thaler, Dong-hyun Lee, Yingbo Zhou, Chetan Ramaiah, Fangxiang Feng, Ruifan Li, Xiaojie Wang, Dimitris Athanasakis, John Shawe-Taylor, Maxim Milakov, John Park, Radu Tudor Ionescu, Marius Popescu, Cristian Grozea, James Bergstra, Jingjing Xie, Lukasz Romaszko, Bing Xu, Chuang Zhang, Yoshua Bengio
2013	—	`conf`	Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms. SciPy James Bergstra, Dan Yamins, David D. Cox
2013	J	`jnl`	Hyperparameter Optimization and Boosting for Classifying Facial Expressions: How good can a "Null" Model be? CoRR James Bergstra, David D. Cox
2013	—	`conf`	Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions for Vision Architectures. ICML (1) James Bergstra, Daniel Yamins, David D. Cox
2013	J	`jnl`	Nengo: a Python tool for building large-scale functional brain models. Frontiers Neuroinformatics Trevor Bekolay, James Bergstra, Eric Hunsberger, Travis DeWolf, Terrence C. Stewart, Daniel Rasmussen, Feng-Xuan Choo, Aaron Voelker, Chris Eliasmith
2013	J	`jnl`	Pylearn2: a machine learning research library. CoRR Ian J. Goodfellow, David Warde-Farley, Pascal Lamblin, Vincent Dumoulin, Mehdi Mirza, Razvan Pascanu, James Bergstra, Frédéric Bastien, Yoshua Bengio
2013	—	`conf`	SkData: Data Sets and Algorithm Evaluation Protocols in Python. SciPy James Bergstra, Nicolas Pinto, David D. Cox
2012	J	`jnl`	Making a Science of Model Search CoRR James Bergstra, Dan Yamins, David D. Cox
2012	J	`jnl`	Random Search for Hyper-Parameter Optimization. J. Mach. Learn. Res. James Bergstra, Yoshua Bengio
2012	J	`jnl`	Theano: new features and speed improvements CoRR Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, James Bergstra, Ian J. Goodfellow, Arnaud Bergeron, Nicolas Bouchard, David Warde-Farley, Yoshua Bengio
2012	—	`conf`	Unsupervised and Transfer Learning Challenge: a Deep Learning Approach. ICML Unsupervised and Transfer Learning Grégoire Mesnil, Yann N. Dauphin, Xavier Glorot, Salah Rifai, Yoshua Bengio, Ian J. Goodfellow, Erick Lavoie, Xavier Muller, Guillaume Desjardins, David Warde-Farley, Pascal Vincent, Aaron C. Courville, James Bergstra
2011	A	`conf`	A Spike and Slab Restricted Boltzmann Machine. AISTATS Aaron C. Courville, James Bergstra, Yoshua Bengio
2011	—	`conf`	Algorithms for Hyper-Parameter Optimization. NIPS James Bergstra, Rémi Bardenet, Yoshua Bengio, Balázs Kégl
2011	J	`jnl`	Suitability of V1 Energy Models for Object Classification. Neural Comput. James Bergstra, Yoshua Bengio, Jérôme Louradour
2011	J	`jnl`	The Statistical Inefficiency of Sparse Coding for Images (or, One Gabor to Rule them All) CoRR James Bergstra, Aaron C. Courville, Yoshua Bengio
2011	A*	`conf`	Unsupervised Models of Images by Spikeand-Slab RBMs. ICML Aaron C. Courville, James Bergstra, Yoshua Bengio
2010	—	`conf`	Scalable Genre and Tag Prediction with Spectral Covariance. ISMIR James Bergstra, Michael I. Mandel, Douglas Eck
2010	—	`conf`	Theano: A CPU and GPU Math Compiler in Python. SciPy James Bergstra, Olivier Breuleux, Frédéric Bastien, Pascal Lamblin, Razvan Pascanu, Guillaume Desjardins, Joseph P. Turian, David Warde-Farley, Yoshua Bengio
2009	—	`conf`	Quadratic Features and Deep Architectures for Chunking. HLT-NAACL (Short Papers) Joseph P. Turian, James Bergstra, Yoshua Bengio
2009	—	`conf`	Slow, Decorrelated Features for Pretraining Complex Cell-like Networks. NIPS James Bergstra, Yoshua Bengio
2007	A*	`conf`	An empirical evaluation of deep architectures on problems with many factors of variation. ICML Hugo Larochelle, Dumitru Erhan, Aaron C. Courville, James Bergstra, Yoshua Bengio
2006	J	`jnl`	Aggregate features and ADABOOSTfor music classification. Mach. Learn. James Bergstra, Norman Casagrande, Dumitru Erhan, Douglas Eck, Balázs Kégl
2006	—	`conf`	Predicting genre labels for artist using FreeDB. ISMIR James Bergstra, Alexandre Lacoste, Douglas Eck