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All publications by Nicol N. Schraudolph
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Variable Metric Stochastic Approximation Theory
Peter Sunehag, Jochen Trumpf, Nicol N. Schraudolph and S.v.n. Vishwanathan
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS-09), 2009


A quasi-Newton approach to non-smooth convex optimization
Jin Yu, Simon Günter, Nicol N. Schraudolph and S.v.n. Vishwanathan
Proceedings of the 25th International Conference on Machine Learning (ICML-08), 2008


Efficient Exact Inference in Planar Ising Models
Nicol N. Schraudolph and Dmitry Kamenetsky
Advances in Neural Information Processing Systems 21, 2008


Fast Iterative Kernel Principal Component Analysis
Simon Günter, Nicol N. Schraudolph and S. Vishwanathan
Journal of Machine Learning Research, 2007


A Stochastic Quasi-Newton Method for Online Convex Optimization
Nicol N. Schraudolph, Jin Yu and Simon Günter
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics (AISTATS-07), 2007


Accelerated training of conditional random fields with stochastic gradient methods
Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy and S.v.n. Vishwanathan
Proceedings of the 23th International Conference on Machine Learning (ICML-06), 2006


Step Size Adaptation in Reproducing Kernel Hilbert Space
S. Vishwanathan, Nicol N. Schraudolph and Alex J. Smola
Journal of Machine Learning Research, 2006


Fast Computation of Graph Kernels
Karsten M. Borgwardt, Nicol N. Schraudolph and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 19, 2006


Fast Iterative Kernel PCA
Nicol N. Schraudolph, Simon Günter and S.v.n. Vishwanathan
Advances in Neural Information Processing Systems 19, 2006


Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation
Jin Yu, Douglas Aberdeen and Nicol N. Schraudolph
Advances in Neural Information Processing Systems 18, 2005


Learning Precise Timing with LSTM Recurrent Networks
Felix A. Gers, Nicol N. Schraudolph and Jürgen Schmidhuber
Journal of Machine Learning Research, 2002