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All publications by Kevin Swersky
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Scalable Bayesian Optimization Using Deep Neural Networks
Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Mostofa Patwary, Mr Prabhat and Ryan Adams
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Generative Moment Matching Networks
Yujia Li, Kevin Swersky and Rich Zemel
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Input Warping for Bayesian Optimization of Non-Stationary Functions
Jasper Snoek, Kevin Swersky, Rich Zemel and Ryan Adams
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Learning Fair Representations
Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi and Cynthia Dwork
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning
Daniel Tarlow, Kevin Swersky, Laurent Charlin, Ilya Sutskever and Rich Zemel
Proceedings of the 30th International Conference on Machine Learning (ICML-13), 2013


Multi-Task Bayesian Optimization
Kevin Swersky, Jasper Snoek and Ryan P. Adams
Advances in Neural Information Processing Systems 26, 2013


Cardinality Restricted Boltzmann Machines
Kevin Swersky, Ilya Sutskever, Daniel Tarlow, Richard S. Zemel, Ruslan Salakhutdinov and Ryan P. Adams
Advances in Neural Information Processing Systems 25, 2012


Probabilistic n-Choose-k Models for Classification and Ranking
Kevin Swersky, Brendan J. Frey, Daniel Tarlow, Richard S. Zemel and Ryan P. Adams
Advances in Neural Information Processing Systems 25, 2012


Estimating the Hessian by Back-propagating Curvature
James Martens, Ilya Sutskever and Kevin Swersky
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


On Autoencoders and Score Matching for Energy Based Models
Kevin Swersky, Marc'aurelio Ranzato, David Buchman, Nando D. Freitas and Benjamin M. Marlin
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011


Inductive Principles for Restricted Boltzmann Machine Learning
Benjamin M. Marlin, Kevin Swersky, Bo Chen and Nando D. Freitas
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010