Nicol N. Schraudolph

According to our database, Nicol N. Schraudolph authored at least 43 papers between 1991 and 2012.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2012

Centering Neural Network Gradient Factors.

Nicol N. Schraudolph

Proceedings of the Neural Networks: Tricks of the Trade - Second Edition, 2012

2010

A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning.

Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph

J. Mach. Learn. Res., 2010

Graph Kernels.

S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt

J. Mach. Learn. Res., 2010

2009

Variable Metric Stochastic Approximation Theory.

Peter Sunehag, Jochen Trumpf, S. V. N. Vishwanathan, Nicol N. Schraudolph

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008

Efficient Exact Inference in Planar Ising Models.

Nicol N. Schraudolph, Dmitry Kamenetsky

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Using stochastic gradient-descent scheme in appearance model based face tracking.

Zhidong Li, Jing Chen, Adrian Chong, Zhenghua Yu, Nicol N. Schraudolph

Proceedings of the International Workshop on Multimedia Signal Processing, 2008

An improved mean-shift tracker with kernel prediction and scale optimisation targeting for low-frame-rate video tracking.

Zhidong Li, Jing Chen, Nicol N. Schraudolph

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

A quasi-Newton approach to non-smooth convex optimization.

Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph

Proceedings of the Machine Learning, 2008

Using an adaptive VAR Model for motion prediction in 3D hand tracking.

Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph

Proceedings of the 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008), 2008

2007

Correction to "Gradient-Based Manipulation of Nonparametric Entropy Estimates" [Jul 04 828-837].

Nicol N. Schraudolph

IEEE Trans. Neural Networks, 2007

A Stochastic Quasi-Newton Method for Online Convex Optimization.

Nicol N. Schraudolph, Jin Yu, Simon Günter

Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Fast Iterative Kernel Principal Component Analysis.

Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan

J. Mach. Learn. Res., 2007

Fast stochastic optimization for articulated structure tracking.

Matthieu Bray, Esther Koller-Meier, Nicol N. Schraudolph, Luc Van Gool

Image Vis. Comput., 2007

3D Hand Tracking in a Stochastic Approximation Setting.

Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph

Proceedings of the Human Motion, 2007

2006

Step Size Adaptation in Reproducing Kernel Hilbert Space.

S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola

J. Mach. Learn. Res., 2006

Measures of Codon Bias in Yeast, the tRNA Pairing Index and Possible DNA Repair Mechanisms.

Markus T. Friberg, Pedro Gonnet, Yves Barral, Nicol N. Schraudolph, Gaston H. Gonnet

Proceedings of the Algorithms in Bioinformatics, 6th International Workshop, 2006

Fast Computation of Graph Kernels.

S. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Fast Iterative Kernel PCA.

Nicol N. Schraudolph, Simon Günter, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Accelerated training of conditional random fields with stochastic gradient methods.

S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy

Proceedings of the Machine Learning, 2006

2005

Accelerating evolutionary algorithms with Gaussian process fitness function models.

Dirk Büche, Nicol N. Schraudolph, Petros Koumoutsakos

IEEE Trans. Syst. Man Cybern. Part C, 2005

Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation.

Nicol N. Schraudolph, Douglas Aberdeen, Jin Yu

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Step size-adapted online support vector learning.

Alexandros Karatzoglou, S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola

Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005

2004

Gradient-based manipulation of nonparametric entropy estimates.

Nicol N. Schraudolph

IEEE Trans. Neural Networks, 2004

Stochastic Meta-Descent for Tracking Articulated Structures.

Matthieu Bray, Esther Koller-Meier, Nicol N. Schraudolph, Luc Van Gool

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2004

2003

Combining Conjugate Direction Methods with Stochastic Approximation of Gradients.

Nicol N. Schraudolph, Thore Graepel

Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003

2002

Fast Curvature Matrix-Vector Products for Second-Order Gradient Descent.

Nicol N. Schraudolph

Neural Comput., 2002

Learning Precise Timing with LSTM Recurrent Networks.

Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber

J. Mach. Learn. Res., 2002

Conjugate Directions for Stochastic Gradient Descent.

Nicol N. Schraudolph, Thore Graepel

Proceedings of the Artificial Neural Networks, 2002

Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems.

Thore Graepel, Nicol N. Schraudolph

Proceedings of the Artificial Neural Networks, 2002

Step size adaptation in evolution strategies using reinforcement learning.

Sibylle D. Müller, Nicol N. Schraudolph, Petros Koumoutsakos

Proceedings of the 2002 Congress on Evolutionary Computation, 2002

2001

Fast Curvature Matrix-Vector Products.

Nicol N. Schraudolph

Proceedings of the Artificial Neural Networks, 2001

Unsupervised Learning in LSTM Recurrent Neural Networks.

Magdalena Klapper-Rybicka, Nicol N. Schraudolph, Jürgen Schmidhuber

Proceedings of the Artificial Neural Networks, 2001

1999

A Fast, Compact Approximation of the Exponential Function.

Nicol N. Schraudolph

Neural Comput., 1999

Online Independent Component Analysis with Local Learning Rate Adaptation.

Nicol N. Schraudolph, Xavier Giannakopoulos

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

1998

Reinforcement Learning with Self-Modifying Policies.

Jürgen Schmidhuber, Jieyu Zhao, Nicol N. Schraudolph

Proceedings of the Learning to Learn., 1998

1996

Centering Neural Network Gradient Factors.

Nicol N. Schraudolph

Proceedings of the Neural Networks: Tricks of the Trade, 1996

1995

Empirical Entropy Manipulation for Real-World Problems.

Paul A. Viola, Nicol N. Schraudolph, Terrence J. Sejnowski

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

Tempering Backpropagation Networks: Not All Weights are Created Equal.

Nicol N. Schraudolph, Terrence J. Sejnowski

Proceedings of the Advances in Neural Information Processing Systems 8, 1995

1994

Plasticity-Mediated Competitive Learning.

Nicol N. Schraudolph, Terrence J. Sejnowski

Proceedings of the Advances in Neural Information Processing Systems 7, 1994

1993

Temporal Difference Learning of Position Evaluation in the Game of Go.

Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski

Proceedings of the Advances in Neural Information Processing Systems 6, 1993

1992

Dynamic Parameter Encoding for Genetic Algorithms.

Nicol N. Schraudolph, Richard K. Belew

Mach. Learn., 1992

Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain.

Nicol N. Schraudolph, Terrence J. Sejnowski

Proceedings of the Advances in Neural Information Processing Systems 5, [NIPS Conference, Denver, Colorado, USA, November 30, 1992

1991

Competitive Anti-Hebbian Learning of Invariants.

Nicol N. Schraudolph, Terrence J. Sejnowski

Proceedings of the Advances in Neural Information Processing Systems 4, 1991