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All publications by Manfred K. Warmuth
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The limits of squared Euclidean distance regularization
Michal Derezinski and Manfred K. Warmuth
Advances in Neural Information Processing Systems 27, 2014


Putting Bayes to sleep
Dmitry Adamskiy, Manfred K. Warmuth and Wouter M. Koolen
Advances in Neural Information Processing Systems 25, 2012


Learning Eigenvectors for Free
Wouter M. Koolen, Wojciech Kotlowski and Manfred K. Warmuth
Advances in Neural Information Processing Systems 24, 2011


Repeated Games against Budgeted Adversaries
Jacob D. Abernethy and Manfred K. Warmuth
Advances in Neural Information Processing Systems 23, 2010


Learning Permutations with Exponential Weights
David P. Helmbold and Manfred K. Warmuth
Journal of Machine Learning Research, 2009


Tutorial summary: Survey of boosting from an optimization perspective
Manfred K. Warmuth and S.v.n. Vishwanathan
Proceedings of the 26th International Conference on Machine Learning (ICML-09), 2009


Winnowing subspaces
Manfred K. Warmuth
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Online kernel PCA with entropic matrix updates
Dima Kuzmin and Manfred K. Warmuth
Proceedings of the 24th International Conference on Machine Learning (ICML-07), 2007


Boosting Algorithms for Maximizing the Soft Margin
Gunnar Rätsch, Manfred K. Warmuth and Karen A. Glocer
Advances in Neural Information Processing Systems 20, 2007


Unlabeled Compression Schemes for Maximum Classes
Dima Kuzmin and Manfred K. Warmuth
Journal of Machine Learning Research, 2007


Totally corrective boosting algorithms that maximize the margin
Manfred K. Warmuth, Jun Liao and Gunnar Rätsch
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension
Manfred K. Warmuth and Dima Kuzmin
Advances in Neural Information Processing Systems 19, 2006


Matrix Exponentiated Gradient Updates for On-line Learning and Bregman Projection
Koji Tsuda, Gunnar Rätsch and Manfred K. Warmuth
Journal of Machine Learning Research, 2005


Efficient Margin Maximizing with Boosting
Gunnar Rätsch and Manfred K. Warmuth
Journal of Machine Learning Research, 2005


A Bayes Rule for Density Matrices
Manfred K. Warmuth
Advances in Neural Information Processing Systems 18, 2005


Matrix Exponential Gradient Updates for On-line Learning and Bregman Projection
Koji Tsuda, Gunnar Rätsch and Manfred K. Warmuth
Advances in Neural Information Processing Systems 17, 2004


Path Kernels and Multiplicative Updates
Eiji Takimoto and Manfred K. Warmuth
Journal of Machine Learning Research, 2003


Boosting versus Covering
Kohei Hatano and Manfred K. Warmuth
Advances in Neural Information Processing Systems 16, 2003


Tracking a Small Set of Experts by Mixing Past Posteriors
Olivier Bousquet and Manfred K. Warmuth
Journal of Machine Learning Research, 2002


Adaptive Caching by Refetching
Robert B. Gramacy, Manfred K. Warmuth, Scott A. Brandt and Ismail Ari
Advances in Neural Information Processing Systems 15, 2002


On the Convergence of Leveraging
Gunnar Rätsch, Sebastian Mika and Manfred K. Warmuth
Advances in Neural Information Processing Systems 14, 2001


Tracking the Best Linear Predictor
Mark Herbster and Manfred K. Warmuth
Journal of Machine Learning Research, 2001