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ORCIDNicol N. Schraudolph
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2010 – 2019
- 2012
[p3]Nicol N. Schraudolph:
Centering Neural Network Gradient Factors. Neural Networks: Tricks of the Trade (2nd ed.) 2012: 205-223- 2010
- [j12]Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph:
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning. J. Mach. Learn. Res. 11: 1145-1200 (2010) - [j11]S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt:
Graph Kernels. J. Mach. Learn. Res. 11: 1201-1242 (2010)
2000 – 2009
- 2009
- [c28]Peter Sunehag, Jochen Trumpf, S. V. N. Vishwanathan, Nicol N. Schraudolph:
Variable Metric Stochastic Approximation Theory. AISTATS 2009: 560-566 - 2008
- [c27]Desmond Chik, Jochen Trumpf
, Nicol N. Schraudolph:
Using an adaptive VAR Model for motion prediction in 3D hand tracking. FG 2008: 1-8 - [c26]Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph:
A quasi-Newton approach to non-smooth convex optimization. ICML 2008: 1216-1223 - [c25]Zhidong Li, Jing Chen, Nicol N. Schraudolph:
An improved mean-shift tracker with kernel prediction and scale optimisation targeting for low-frame-rate video tracking. ICPR 2008: 1-4 - [c24]Zhidong Li, Jing Chen, Adrian Chong, Zhenghua Yu, Nicol N. Schraudolph:
Using stochastic gradient-descent scheme in appearance model based face tracking. MMSP 2008: 640-645 - [c23]Nicol N. Schraudolph, Dmitry Kamenetsky:
Efficient Exact Inference in Planar Ising Models. NIPS 2008: 1417-1424 - [i2]S. V. N. Vishwanathan, Karsten M. Borgwardt, Imre Risi Kondor, Nicol N. Schraudolph:
Graph Kernels. CoRR abs/0807.0093 (2008) - [i1]Nicol N. Schraudolph, Dmitry Kamenetsky:
Efficient Exact Inference in Planar Ising Models. CoRR abs/0810.4401 (2008) - 2007
- [j10]Matthieu Bray, Esther Koller-Meier, Nicol N. Schraudolph, Luc Van Gool:
Fast stochastic optimization for articulated structure tracking. Image Vis. Comput. 25(3): 352-364 (2007) - [j9]Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan:
Fast Iterative Kernel Principal Component Analysis. J. Mach. Learn. Res. 8: 1893-1918 (2007) - [j8]Nicol N. Schraudolph:
Correction to "Gradient-Based Manipulation of Nonparametric Entropy Estimates" [Jul 04 828-837]. IEEE Trans. Neural Networks 18(2): 609 (2007) - [c22]Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph:
3D Hand Tracking in a Stochastic Approximation Setting. Workshop on Human Motion 2007: 136-151 - [c21]Nicol N. Schraudolph, Jin Yu, Simon Günter:
A Stochastic Quasi-Newton Method for Online Convex Optimization. AISTATS 2007: 436-443 - 2006
- [j7]S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola:
Step Size Adaptation in Reproducing Kernel Hilbert Space. J. Mach. Learn. Res. 7: 1107-1133 (2006) - [c20]S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy:
Accelerated training of conditional random fields with stochastic gradient methods. ICML 2006: 969-976 - [c19]Nicol N. Schraudolph, Simon Günter, S. V. N. Vishwanathan:
Fast Iterative Kernel PCA. NIPS 2006: 1225-1232 - [c18]S. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph:
Fast Computation of Graph Kernels. NIPS 2006: 1449-1456 - [c17]Markus T. Friberg, Pedro Gonnet, Yves Barral, Nicol N. Schraudolph, Gaston H. Gonnet:
Measures of Codon Bias in Yeast, the tRNA Pairing Index and Possible DNA Repair Mechanisms. WABI 2006: 1-11 - 2005
- [j6]Dirk Büche, Nicol N. Schraudolph, Petros Koumoutsakos:
Accelerating evolutionary algorithms with Gaussian process fitness function models. IEEE Trans. Syst. Man Cybern. Part C 35(2): 183-194 (2005) - [c16]Alexandros Karatzoglou, S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola:
Step size-adapted online support vector learning. ISSPA 2005: 823-826 - [c15]Nicol N. Schraudolph, Douglas Aberdeen, Jin Yu:
Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation. NIPS 2005: 1185-1192 - 2004
- [j5]Nicol N. Schraudolph:
Gradient-based manipulation of nonparametric entropy estimates. IEEE Trans. Neural Networks 15(4): 828-837 (2004) - [c14]Matthieu Bray, Esther Koller-Meier, Nicol N. Schraudolph, Luc Van Gool:
Stochastic Meta-Descent for Tracking Articulated Structures. CVPR Workshops 2004: 7 - 2003
- [c13]Nicol N. Schraudolph, Thore Graepel:
Combining Conjugate Direction Methods with Stochastic Approximation of Gradients. AISTATS 2003: 248-253 - 2002
- [j4]Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber:
Learning Precise Timing with LSTM Recurrent Networks. J. Mach. Learn. Res. 3: 115-143 (2002) - [j3]Nicol N. Schraudolph:
Fast Curvature Matrix-Vector Products for Second-Order Gradient Descent. Neural Comput. 14(7): 1723-1738 (2002) - [c12]Sibylle D. Müller, Nicol N. Schraudolph, Petros Koumoutsakos:
Step size adaptation in evolution strategies using reinforcement learning. IEEE Congress on Evolutionary Computation 2002: 151-156 - [c11]Thore Graepel, Nicol N. Schraudolph:
Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems. ICANN 2002: 450-455 - [c10]Nicol N. Schraudolph, Thore Graepel:
Conjugate Directions for Stochastic Gradient Descent. ICANN 2002: 1351-1358 - 2001
- [c9]Nicol N. Schraudolph:
Fast Curvature Matrix-Vector Products. ICANN 2001: 19-26 - [c8]Magdalena Klapper-Rybicka, Nicol N. Schraudolph, Jürgen Schmidhuber:
Unsupervised Learning in LSTM Recurrent Neural Networks. ICANN 2001: 684-691
1990 – 1999
- 1999
- [j2]Nicol N. Schraudolph:
A Fast, Compact Approximation of the Exponential Function. Neural Comput. 11(4): 853-862 (1999) - [c7]Nicol N. Schraudolph, Xavier Giannakopoulos:
Online Independent Component Analysis with Local Learning Rate Adaptation. NIPS 1999: 789-795 - 1998
- [p2]Jürgen Schmidhuber, Jieyu Zhao, Nicol N. Schraudolph:
Reinforcement Learning with Self-Modifying Policies. Learning to Learn 1998: 293-309 - 1996
- [p1]Nicol N. Schraudolph:
Centering Neural Network Gradient Factors. Neural Networks: Tricks of the Trade 1996: 207-226 - 1995
- [c6]Nicol N. Schraudolph, Terrence J. Sejnowski:
Tempering Backpropagation Networks: Not All Weights are Created Equal. NIPS 1995: 563-569 - [c5]Paul A. Viola, Nicol N. Schraudolph, Terrence J. Sejnowski:
Empirical Entropy Manipulation for Real-World Problems. NIPS 1995: 851-857 - 1994
- [c4]Nicol N. Schraudolph, Terrence J. Sejnowski:
Plasticity-Mediated Competitive Learning. NIPS 1994: 475-480 - 1993
- [c3]Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski:
Temporal Difference Learning of Position Evaluation in the Game of Go. NIPS 1993: 817-824 - 1992
- [j1]Nicol N. Schraudolph, Richard K. Belew:
Dynamic Parameter Encoding for Genetic Algorithms. Mach. Learn. 9: 9-21 (1992) - [c2]Nicol N. Schraudolph, Terrence J. Sejnowski:
Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain. NIPS 1992: 499-506 - 1991
- [c1]Nicol N. Schraudolph, Terrence J. Sejnowski:
Competitive Anti-Hebbian Learning of Invariants. NIPS 1991: 1017-1024
Coauthor Index
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