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All publications by Robert C. Williamson
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Learning with Symmetric Label Noise: The Importance of Being Unhinged
Brendan V. Rooyen, Aditya Menon and Robert C. Williamson
Advances in Neural Information Processing Systems 28, 2015


From Stochastic Mixability to Fast Rates
Nishant A. Mehta and Robert C. Williamson
Advances in Neural Information Processing Systems 27, 2014


Mixability in Statistical Learning
Tim V. Erven, Peter Grünwald, Mark D. Reid and Robert C. Williamson
Advances in Neural Information Processing Systems 25, 2012


The Convexity and Design of Composite Multiclass Losses
Peng Sun, Mark D. Reid and Robert C. Williamson
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Composite Multiclass Losses
Elodie Vernet, Mark D. Reid and Robert C. Williamson
Advances in Neural Information Processing Systems 24, 2011


Convexity of Proper Composite Binary Losses
Mark D. Reid and Robert C. Williamson
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS-10), 2010


Surrogate regret bounds for proper losses
Mark D. Reid and Robert C. Williamson
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


The Need for Open Source Software in Machine Learning
Sören Sonnenburg, Mikio L. Braun, Cheng S. Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann Lecun, Klaus-robert Müller, Fernando Pereira, Carl E. Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Pascal Vincent, Jason Weston, Robert C. Williamson and Alex J. Smola
Journal of Machine Learning Research, 2007


Learning the Kernel with Hyperkernels
Cheng S. Ong, Robert C. Williamson and Alex J. Smola
Journal of Machine Learning Research, 2005


Hyperkernels
Cheng S. Ong, Robert C. Williamson and Alex J. Smola
Advances in Neural Information Processing Systems 15, 2002


Algorithmic Luckiness
Ralf Herbrich and Robert C. Williamson
Journal of Machine Learning Research, 2002


Algorithmic Luckiness
Ralf Herbrich and Robert C. Williamson
Advances in Neural Information Processing Systems 14, 2001


Kernel Machines and Boolean Functions
Adam Kowalczyk, Alex J. Smola and Robert C. Williamson
Advances in Neural Information Processing Systems 14, 2001


Online Learning with Kernels
Jyrki Kivinen, Alex J. Smola and Robert C. Williamson
Advances in Neural Information Processing Systems 14, 2001


Regularized Principal Manifolds
Alex J. Smola, Sebastian Mika, Bernhard Schölkopf and Robert C. Williamson
Journal of Machine Learning Research, 2001


Prior Knowledge and Preferential Structures in Gradient Descent Learning Algorithms
Robert E. Mahony and Robert C. Williamson
Journal of Machine Learning Research, 2001