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Nicol N. Schraudolph: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Nicol N. Schraudolph, Richard K. Belew
    Dynamic Parameter Encoding for Genetic Algorithms. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1992, v:9, n:, pp:9-21 [Journal]
  2. Thore Graepel, Nicol N. Schraudolph
    Stable Adaptive Momentum for Rapid Online Learning in Nonlinear Systems. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:450-455 [Conf]
  3. Magdalena Klapper-Rybicka, Nicol N. Schraudolph, Jürgen Schmidhuber
    Unsupervised Learning in LSTM Recurrent Neural Networks. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:684-691 [Conf]
  4. Nicol N. Schraudolph
    Fast Curvature Matrix-Vector Products. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:19-26 [Conf]
  5. Nicol N. Schraudolph, Thore Graepel
    Conjugate Directions for Stochastic Gradient Descent. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:1351-1358 [Conf]
  6. S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
    Accelerated training of conditional random fields with stochastic gradient methods. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:969-976 [Conf]
  7. Nicol N. Schraudolph
    Centering Neural Network Gradient Factors. [Citation Graph (0, 0)][DBLP]
    Neural Networks: Tricks of the Trade, 1996, pp:207-226 [Conf]
  8. Nicol N. Schraudolph, Douglas Aberdeen, Jin Yu
    Fast Online Policy Gradient Learning with SMD Gain Vector Adaptation. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  9. Nicol N. Schraudolph, Peter Dayan, Terrence J. Sejnowski
    Temporal Difference Learning of Position Evaluation in the Game of Go. [Citation Graph (0, 0)][DBLP]
    NIPS, 1993, pp:817-824 [Conf]
  10. Nicol N. Schraudolph, Xavier Giannakopoulos
    Online Independent Component Analysis with Local Learning Rate Adaptation. [Citation Graph (0, 0)][DBLP]
    NIPS, 1999, pp:789-795 [Conf]
  11. Nicol N. Schraudolph, Terrence J. Sejnowski
    Competitive Anti-Hebbian Learning of Invariants. [Citation Graph (0, 0)][DBLP]
    NIPS, 1991, pp:1017-1024 [Conf]
  12. Nicol N. Schraudolph, Terrence J. Sejnowski
    Unsupervised Discrimination of Clustered Data via Optimization of Binary Information Gain. [Citation Graph (0, 0)][DBLP]
    NIPS, 1992, pp:499-506 [Conf]
  13. Nicol N. Schraudolph, Terrence J. Sejnowski
    Plasticity-Mediated Competitive Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:475-480 [Conf]
  14. Nicol N. Schraudolph, Terrence J. Sejnowski
    Tempering Backpropagation Networks: Not All Weights are Created Equal. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:563-569 [Conf]
  15. Paul A. Viola, Nicol N. Schraudolph, Terrence J. Sejnowski
    Empirical Entropy Manipulation for Real-World Problems. [Citation Graph (0, 0)][DBLP]
    NIPS, 1995, pp:851-857 [Conf]
  16. 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. [Citation Graph (0, 0)][DBLP]
    WABI, 2006, pp:1-11 [Conf]
  17. Matthieu Bray, Esther Koller-Meier, Nicol N. Schraudolph, Luc J. Van Gool
    Fast stochastic optimization for articulated structure tracking. [Citation Graph (0, 0)][DBLP]
    Image Vision Comput., 2007, v:25, n:3, pp:352-364 [Journal]
  18. Felix A. Gers, Nicol N. Schraudolph, Jürgen Schmidhuber
    Learning Precise Timing with LSTM Recurrent Networks. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:115-143 [Journal]
  19. S. V. N. Vishwanathan, Nicol N. Schraudolph, Alex J. Smola
    Step Size Adaptation in Reproducing Kernel Hilbert Space. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:7, n:, pp:1107-1133 [Journal]
  20. Nicol N. Schraudolph
    Fast Curvature Matrix-Vector Products for Second-Order Gradient Descent. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2002, v:14, n:7, pp:1723-1738 [Journal]
  21. Nicol N. Schraudolph
    A Fast, Compact Approximation of the Exponential Function. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 1999, v:11, n:4, pp:853-862 [Journal]
  22. Dirk Büche, Nicol N. Schraudolph, Petros Koumoutsakos
    Accelerating evolutionary algorithms with Gaussian process fitness function models. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part C, 2005, v:35, n:2, pp:183-194 [Journal]
  23. Desmond Chik, Jochen Trumpf, Nicol N. Schraudolph
    3D Hand Tracking in a Stochastic Approximation Setting. [Citation Graph (0, 0)][DBLP]
    Workshop on Human Motion, 2007, pp:136-151 [Conf]
  24. S. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph
    Fast Computation of Graph Kernels. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1449-1456 [Conf]
  25. Nicol N. Schraudolph, Simon Günter, S. V. N. Vishwanathan
    Fast Iterative Kernel PCA. [Citation Graph (0, 0)][DBLP]
    NIPS, 2006, pp:1225-1232 [Conf]

  26. Using an adaptive VAR Model for motion prediction in 3D hand tracking. [Citation Graph (, )][DBLP]


  27. A quasi-Newton approach to non-smooth convex optimization. [Citation Graph (, )][DBLP]


  28. An improved mean-shift tracker with kernel prediction and scale optimisation targeting for low-frame-rate video tracking. [Citation Graph (, )][DBLP]


  29. Efficient Exact Inference in Planar Ising Models. [Citation Graph (, )][DBLP]


  30. Using stochastic gradient-descent scheme in appearance model based face tracking. [Citation Graph (, )][DBLP]


  31. Graph Kernels [Citation Graph (, )][DBLP]


  32. Efficient Exact Inference in Planar Ising Models [Citation Graph (, )][DBLP]


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