2008 |
33 | EE | Desmond Chik,
Jochen Trumpf,
Nicol N. Schraudolph:
Using an adaptive VAR Model for motion prediction in 3D hand tracking.
FG 2008: 1-8 |
32 | EE | Jin Yu,
S. V. N. Vishwanathan,
Simon Günter,
Nicol N. Schraudolph:
A quasi-Newton approach to non-smooth convex optimization.
ICML 2008: 1216-1223 |
31 | EE | 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 |
30 | EE | 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 |
29 | EE | Nicol N. Schraudolph,
Dmitry Kamenetsky:
Efficient Exact Inference in Planar Ising Models.
NIPS 2008: 1417-1424 |
28 | EE | S. V. N. Vishwanathan,
Karsten M. Borgwardt,
Risi Imre Kondor,
Nicol N. Schraudolph:
Graph Kernels
CoRR abs/0807.0093: (2008) |
27 | EE | Nicol N. Schraudolph,
Dmitry Kamenetsky:
Efficient Exact Inference in Planar Ising Models
CoRR abs/0810.4401: (2008) |
2007 |
26 | EE | Desmond Chik,
Jochen Trumpf,
Nicol N. Schraudolph:
3D Hand Tracking in a Stochastic Approximation Setting.
Workshop on Human Motion 2007: 136-151 |
25 | EE | Nicol N. Schraudolph:
Correction to "Gradient-Based Manipulation of Nonparametric Entropy Estimates" [Jul 04 828-837].
IEEE Transactions on Neural Networks 18(2): 609 (2007) |
24 | EE | Matthieu Bray,
Esther Koller-Meier,
Nicol N. Schraudolph,
Luc J. Van Gool:
Fast stochastic optimization for articulated structure tracking.
Image Vision Comput. 25(3): 352-364 (2007) |
2006 |
23 | EE | 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 |
22 | EE | Nicol N. Schraudolph,
Simon Günter,
S. V. N. Vishwanathan:
Fast Iterative Kernel PCA.
NIPS 2006: 1225-1232 |
21 | EE | S. V. N. Vishwanathan,
Karsten M. Borgwardt,
Nicol N. Schraudolph:
Fast Computation of Graph Kernels.
NIPS 2006: 1449-1456 |
20 | EE | 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 |
19 | EE | S. V. N. Vishwanathan,
Nicol N. Schraudolph,
Alex J. Smola:
Step Size Adaptation in Reproducing Kernel Hilbert Space.
Journal of Machine Learning Research 7: 1107-1133 (2006) |
2005 |
18 | EE | Nicol N. Schraudolph,
Douglas Aberdeen,
Jin Yu:
Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation.
NIPS 2005 |
17 | EE | Dirk Büche,
Nicol N. Schraudolph,
Petros Koumoutsakos:
Accelerating evolutionary algorithms with Gaussian process fitness function models.
IEEE Transactions on Systems, Man, and Cybernetics, Part C 35(2): 183-194 (2005) |
2002 |
16 | EE | Nicol N. Schraudolph,
Thore Graepel:
Conjugate Directions for Stochastic Gradient Descent.
ICANN 2002: 1351-1358 |
15 | EE | Thore Graepel,
Nicol N. Schraudolph:
Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems.
ICANN 2002: 450-455 |
14 | EE | Felix A. Gers,
Nicol N. Schraudolph,
Jürgen Schmidhuber:
Learning Precise Timing with LSTM Recurrent Networks.
Journal of Machine Learning Research 3: 115-143 (2002) |
13 | EE | Nicol N. Schraudolph:
Fast Curvature Matrix-Vector Products for Second-Order Gradient Descent.
Neural Computation 14(7): 1723-1738 (2002) |
2001 |
12 | EE | Nicol N. Schraudolph:
Fast Curvature Matrix-Vector Products.
ICANN 2001: 19-26 |
11 | EE | Magdalena Klapper-Rybicka,
Nicol N. Schraudolph,
Jürgen Schmidhuber:
Unsupervised Learning in LSTM Recurrent Neural Networks.
ICANN 2001: 684-691 |
1999 |
10 | EE | Nicol N. Schraudolph,
Xavier Giannakopoulos:
Online Independent Component Analysis with Local Learning Rate Adaptation.
NIPS 1999: 789-795 |
9 | | Nicol N. Schraudolph:
A Fast, Compact Approximation of the Exponential Function.
Neural Computation 11(4): 853-862 (1999) |
1996 |
8 | EE | Nicol N. Schraudolph:
Centering Neural Network Gradient Factors.
Neural Networks: Tricks of the Trade 1996: 207-226 |
1995 |
7 | EE | Nicol N. Schraudolph,
Terrence J. Sejnowski:
Tempering Backpropagation Networks: Not All Weights are Created Equal.
NIPS 1995: 563-569 |
6 | EE | Paul A. Viola,
Nicol N. Schraudolph,
Terrence J. Sejnowski:
Empirical Entropy Manipulation for Real-World Problems.
NIPS 1995: 851-857 |
1994 |
5 | EE | Nicol N. Schraudolph,
Terrence J. Sejnowski:
Plasticity-Mediated Competitive Learning.
NIPS 1994: 475-480 |
1993 |
4 | EE | Nicol N. Schraudolph,
Peter Dayan,
Terrence J. Sejnowski:
Temporal Difference Learning of Position Evaluation in the Game of Go.
NIPS 1993: 817-824 |
1992 |
3 | EE | Nicol N. Schraudolph,
Terrence J. Sejnowski:
Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain.
NIPS 1992: 499-506 |
2 | | Nicol N. Schraudolph,
Richard K. Belew:
Dynamic Parameter Encoding for Genetic Algorithms.
Machine Learning 9: 9-21 (1992) |
1991 |
1 | EE | Nicol N. Schraudolph,
Terrence J. Sejnowski:
Competitive Anti-Hebbian Learning of Invariants.
NIPS 1991: 1017-1024 |