Nicol N. Schraudolph

Nicol N. Schraudolph, T. Graepel, T. Graepel, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Step Size Adaptation in Reproducing Kernel Hilbert Space

Alexander J. Smola, S. V. N. Vishwanathan, Nicol N. Schraudolph, 2006, J. Mach. Learn. Res..

Fast Iterative Kernel Principal Component Analysis

S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph, 2007, J. Mach. Learn. Res..

Empirical Entropy Manipulation for Real-World Problems

Paul A. Viola, Terrence J. Sejnowski, Nicol N. Schraudolph, 1995, NIPS.

Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain

Terrence J. Sejnowski, Nicol N. Schraudolph, T. Sejnowski, 1992, NIPS.

Online Local Gain Adaptation for Multi-Layer Perceptrons

Nicol N. Schraudolph, N. Schraudolph, 1998 .

Step size-adapted online support vector learning

Alexander J. Smola, S. V. N. Vishwanathan, Alexandros Karatzoglou, 2005, Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005..

Plasticity-Mediated Competitive Learning

Terrence J. Sejnowski, Nicol N. Schraudolph, 1994, NIPS.

Fast Curvature Matrix-Vector Products

Nicol N. Schraudolph, 2001, ICANN.

Online Independent Component Analysis with Local Learning Rate Adaptation

Nicol N. Schraudolph, Xavier Giannakopoulos, 1999, NIPS.

Combining Conjugate Direction Methods with Stochastic Approximation of Gradients

Nicol N. Schraudolph, Thore Graepel, T. Graepel, 2003, AISTATS.

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

Nicol N. Schraudolph, Jochen Trumpf, Desmond Chik, 2008, 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition.

Centering Neural Network Gradient Factors

Nicol N. Schraudolph, N. Schraudolph, 1996, Neural Networks.

A Stochastic Quasi-Newton Method for Online Convex Optimization

Simon Günter, Nicol N. Schraudolph, Jin Yu, 2007, AISTATS.

Centering Neural Network Gradient Factors

Nicol N. Schraudolph, N. Schraudolph, 1996, Neural Networks: Tricks of the Trade.

Accelerating evolutionary algorithms with Gaussian process fitness function models

Petros Koumoutsakos, Nicol N. Schraudolph, Dirk Büche, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Temporal Difference Learning of Position Evaluation in the Game of Go

Terrence J. Sejnowski, Peter Dayan, Nicol N. Schraudolph, 1993, NIPS.

A Generic Dataflow Programming Environment for Neural Networks

Nicol N. Schraudolph, 2000 .

Scoring Conference Submissions by Alternate Maximization of Likelihood

Nicol N. Schraudolph, 1998 .

Efficient Exact Inference in Planar Ising Models

Nicol N. Schraudolph, Dmitry Kamenetsky, N. Schraudolph, 2008, NIPS.

Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems

Nicol N. Schraudolph, Thore Graepel, 2002, ICANN.

Reinforcement Learning with Self-Modifying Policies

Jürgen Schmidhuber, Jieyu Zhao, Nicol N. Schraudolph, 1998, Learning to Learn.

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

S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph, 2008, J. Mach. Learn. Res..

Stochastic optimisation for high-dimensional tracking in dense range maps

Nicol N. Schraudolph, Matthieu Bray, Esther Koller-Meier, 2005 .

3D Hand Tracking in a Stochastic Approximation Setting

Nicol N. Schraudolph, Jochen Trumpf, Desmond Chik, 2007, Workshop on Human Motion.

Learning to evaluate Go positions via temporal difference methods

Terrence J. Sejnowski, Peter Dayan, Nicol N. Schraudolph, 2001 .

Conjugate Directions for Stochastic Gradient Descent

Nicol N. Schraudolph, Thore Graepel, 2002, ICANN.

Accelerated Gradient Descent by Factor-Centering Decomposition

Nicol N. Schraudolph, N. Schraudolph, 1998 .

A quasi-Newton approach to non-smooth convex optimization

S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph, 2008, ICML '08.

Fast Computation of Graph Kernels

S. V. N. Vishwanathan, Nicol N. Schraudolph, Karsten M. Borgwardt, 2006, NIPS.

Accelerated training of conditional random fields with stochastic gradient methods

Mark W. Schmidt, S. V. N. Vishwanathan, Kevin P. Murphy, 2006, ICML.

Fast stochastic optimization for articulated structure tracking

Luc Van Gool, Nicol N. Schraudolph, Matthieu Bray, 2007, Image Vis. Comput..

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

Gaston H. Gonnet, Nicol N. Schraudolph, Pedro Gonnet, 2006, WABI.

Gradient-based manipulation of nonparametric entropy estimates

Nicol N. Schraudolph, N. Schraudolph, 2004, IEEE Transactions on Neural Networks.

Tempering Backpropagation Networks: Not All Weights are Created Equal

Terrence J. Sejnowski, Nicol N. Schraudolph, T. Sejnowski, 1995, NIPS.

Graph kernels

S. V. N. Vishwanathan, Nicol N. Schraudolph, Karsten M. Borgwardt, 2007 .

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

Nicol N. Schraudolph, N. Schraudolph, 2002, Neural Computation.

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, 2008, 2008 19th International Conference on Pattern Recognition.

Gradient-Based Manipulation of

Nicol N. Schraudolph, N. Schraudolph, 2004 .

Unsupervised Learning in Recurrent Neural Networks

Jürgen Schmidhuber, Nicol N. Schraudolph, Magdalena Klapper-Rybicka, 2001 .

Unsupervised Recurrent Neural Networks

Nicol N. Schraudolph, Juergen Schmidhuber, Magdalena Klapper-Rybicka, 2000 .

Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation

Nicol N. Schraudolph, Jin Yu, Douglas Aberdeen, 2005, NIPS.

Unsupervised Learning in LSTM Recurrent Neural Networks

Jürgen Schmidhuber, Nicol N. Schraudolph, Magdalena Klapper-Rybicka, 2001, ICANN.

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

Nicol N. Schraudolph, N. Schraudolph, 2007, IEEE Trans. Neural Networks.

Competitive Anti-Hebbian Learning of Invariants

Terrence J. Sejnowski, Nicol N. Schraudolph, T. Sejnowski, 1991, NIPS.

Fast Iterative Kernel PCA

S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph, 2006, NIPS.

A Role for Codon Order in Translation Dynamics

Nicol N. Schraudolph, Pedro Gonnet, Peter von Rohr, 2010, Cell.