Nicol N. Schraudolph

45 papers A* 2A 3B 3C 6Journal 14Unranked 14

Year	Rank	Type	Title / Venue / Authors
2012	—	`ch.`	Centering Neural Network Gradient Factors. Neural Networks: Tricks of the Trade (2nd ed.) Nicol N. Schraudolph
2010	J	`jnl`	A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning. J. Mach. Learn. Res. Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph
2010	J	`jnl`	Graph Kernels. J. Mach. Learn. Res. S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt
2009	A	`conf`	Variable Metric Stochastic Approximation Theory. AISTATS Peter Sunehag, Jochen Trumpf, S. V. N. Vishwanathan, Nicol N. Schraudolph
2008	A*	`conf`	A quasi-Newton approach to non-smooth convex optimization. ICML Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph
2008	B	`conf`	An improved mean-shift tracker with kernel prediction and scale optimisation targeting for low-frame-rate video tracking. ICPR Zhidong Li, Jing Chen, Nicol N. Schraudolph
2008	J	`jnl`	Efficient Exact Inference in Planar Ising Models CoRR Nicol N. Schraudolph, Dmitry Kamenetsky
2008	—	`conf`	Efficient Exact Inference in Planar Ising Models. NIPS Nicol N. Schraudolph, Dmitry Kamenetsky
2008	J	`jnl`	Graph Kernels CoRR S. V. N. Vishwanathan, Karsten M. Borgwardt, Imre Risi Kondor, Nicol N. Schraudolph
2008	B	`conf`	Using an adaptive VAR Model for motion prediction in 3D hand tracking. FG Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph
2008	C	`conf`	Using stochastic gradient-descent scheme in appearance model based face tracking. MMSP Zhidong Li, Jing Chen, Adrian Chong, Zhenghua Yu, Nicol N. Schraudolph
2007	—	`conf`	3D Hand Tracking in a Stochastic Approximation Setting. Workshop on Human Motion Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph
2007	A	`conf`	A Stochastic Quasi-Newton Method for Online Convex Optimization. AISTATS Nicol N. Schraudolph, Jin Yu, Simon Günter
2007	J	`jnl`	Correction to "Gradient-Based Manipulation of Nonparametric Entropy Estimates" [Jul 04 828-837]. IEEE Trans. Neural Networks Nicol N. Schraudolph
2007	J	`jnl`	Fast Iterative Kernel Principal Component Analysis. J. Mach. Learn. Res. Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan
2007	J	`jnl`	Fast stochastic optimization for articulated structure tracking. Image Vis. Comput. Matthieu Bray, Esther Koller-Meier, Nicol N. Schraudolph, Luc Van Gool
2006	A*	`conf`	Accelerated training of conditional random fields with stochastic gradient methods. ICML S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
2006	—	`conf`	Fast Computation of Graph Kernels. NIPS S. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph
2006	—	`conf`	Fast Iterative Kernel PCA. NIPS Nicol N. Schraudolph, Simon Günter, S. V. N. Vishwanathan
2006	C	`conf`	Measures of Codon Bias in Yeast, the tRNA Pairing Index and Possible DNA Repair Mechanisms. WABI Markus T. Friberg, Pedro Gonnet, Yves Barral, Nicol N. Schraudolph, Gaston H. Gonnet
2006	J	`jnl`	Step Size Adaptation in Reproducing Kernel Hilbert Space. J. Mach. Learn. Res. S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola
2005	J	`jnl`	Accelerating evolutionary algorithms with Gaussian process fitness function models. IEEE Trans. Syst. Man Cybern. Part C Dirk Büche, Nicol N. Schraudolph, Petros Koumoutsakos
2005	—	`conf`	Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation. NIPS Nicol N. Schraudolph, Douglas Aberdeen, Jin Yu
2005	—	`conf`	Step size-adapted online support vector learning. ISSPA Alexandros Karatzoglou, S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola
2004	J	`jnl`	Gradient-based manipulation of nonparametric entropy estimates. IEEE Trans. Neural Networks Nicol N. Schraudolph
2004	—	`conf`	Stochastic Meta-Descent for Tracking Articulated Structures. CVPR Workshops Matthieu Bray, Esther Koller-Meier, Nicol N. Schraudolph, Luc Van Gool
2003	A	`conf`	Combining Conjugate Direction Methods with Stochastic Approximation of Gradients. AISTATS Nicol N. Schraudolph, Thore Graepel
2002	C	`conf`	Conjugate Directions for Stochastic Gradient Descent. ICANN Nicol N. Schraudolph, Thore Graepel
2002	J	`jnl`	Fast Curvature Matrix-Vector Products for Second-Order Gradient Descent. Neural Comput. Nicol N. Schraudolph
2002	J	`jnl`	Learning Precise Timing with LSTM Recurrent Networks. J. Mach. Learn. Res. Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber
2002	C	`conf`	Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems. ICANN Thore Graepel, Nicol N. Schraudolph
2002	B	`conf`	Step size adaptation in evolution strategies using reinforcement learning. IEEE Congress on Evolutionary Computation Sibylle D. Müller, Nicol N. Schraudolph, Petros Koumoutsakos
2001	C	`conf`	Fast Curvature Matrix-Vector Products. ICANN Nicol N. Schraudolph
2001	C	`conf`	Unsupervised Learning in LSTM Recurrent Neural Networks. ICANN Magdalena Klapper-Rybicka, Nicol N. Schraudolph, Jürgen Schmidhuber
1999	J	`jnl`	A Fast, Compact Approximation of the Exponential Function. Neural Comput. Nicol N. Schraudolph
1999	—	`conf`	Online Independent Component Analysis with Local Learning Rate Adaptation. NIPS Nicol N. Schraudolph, Xavier Giannakopoulos
1998	—	`ch.`	Reinforcement Learning with Self-Modifying Policies. Learning to Learn Jürgen Schmidhuber, Jieyu Zhao, Nicol N. Schraudolph
1996	—	`ch.`	Centering Neural Network Gradient Factors. Neural Networks: Tricks of the Trade Nicol N. Schraudolph
1995	—	`conf`	Empirical Entropy Manipulation for Real-World Problems. NIPS Paul A. Viola, Nicol N. Schraudolph, Terrence J. Sejnowski
1995	—	`conf`	Tempering Backpropagation Networks: Not All Weights are Created Equal. NIPS Nicol N. Schraudolph, Terrence J. Sejnowski
1994	—	`conf`	Plasticity-Mediated Competitive Learning. NIPS Nicol N. Schraudolph, Terrence J. Sejnowski
1993	—	`conf`	Temporal Difference Learning of Position Evaluation in the Game of Go. NIPS Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski
1992	J	`jnl`	Dynamic Parameter Encoding for Genetic Algorithms. Mach. Learn. Nicol N. Schraudolph, Richard K. Belew
1992	—	`conf`	Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain. NIPS Nicol N. Schraudolph, Terrence J. Sejnowski
1991	—	`conf`	Competitive Anti-Hebbian Learning of Invariants. NIPS Nicol N. Schraudolph, Terrence J. Sejnowski