| 2009 |
|---|
| 103 | EE | Paul von Bünau,
Frank C. Meinecke,
Klaus-Robert Müller:
Stationary Subspace Analysis.
ICA 2009: 1-8 |
| 2008 |
|---|
| 102 | EE | Vojtech Franc,
Pavel Laskov,
Klaus-Robert Müller:
Stopping conditions for exact computation of leave-one-out error in support vector machines.
ICML 2008: 328-335 |
| 101 | EE | Konrad Rieck,
Stefan Wahl,
Pavel Laskov,
Peter Domschitz,
Klaus-Robert Müller:
A Self-learning System for Detection of Anomalous SIP Messages.
IPTComm 2008: 90-106 |
| 100 | EE | Michael Tangermann,
Matthias Krauledat,
Konrad Grzeska,
Max Sagebaum,
Benjamin Blankertz,
Carmen Vidaurre,
Klaus-Robert Müller:
Playing Pinball with non-invasive BCI.
NIPS 2008: 1641-1648 |
| 99 | EE | Stefan Haufe,
Vadim V. Nikulin,
Andreas Ziehe,
Klaus-Robert Müller,
Guido Nolte:
Estimating vector fields using sparse basis field expansions.
NIPS 2008: 617-624 |
| 98 | EE | Benjamin Blankertz,
Michael Tangermann,
Florin Popescu,
Matthias Krauledat,
Siamac Fazli,
Márton Dónaczy,
Gabriel Curio,
Klaus-Robert Müller:
The Berlin Brain-Computer Interface.
WCCI 2008: 79-101 |
| 97 | EE | Anton Nijholt,
Desney S. Tan,
Gert Pfurtscheller,
Clemens Brunner,
José del R. Millán,
Brendan Allison,
Bernhard Graimann,
Florin Popescu,
Benjamin Blankertz,
Klaus-Robert Müller:
Brain-Computer Interfacing for Intelligent Systems.
IEEE Intelligent Systems 23(3): 72-79 (2008) |
| 96 | EE | Masashi Sugiyama,
Motoaki Kawanabe,
Gilles Blanchard,
Klaus-Robert Müller:
Approximating the Best Linear Unbiased Estimator of Non-Gaussian Signals with Gaussian Noise.
IEICE Transactions 91-D(5): 1577-1580 (2008) |
| 2007 |
|---|
| 95 | EE | Benjamin Blankertz,
Matthias Krauledat,
Guido Dornhege,
John Williamson,
Roderick Murray-Smith,
Klaus-Robert Müller:
A Note on Brain Actuated Spelling with the Berlin Brain-Computer Interface.
HCI (6) 2007: 759-768 |
| 94 | EE | Klaus-Robert Müller,
Matthias Krauledat,
Guido Dornhege,
Gabriel Curio,
Benjamin Blankertz:
Machine Learning and Applications for Brain-Computer Interfacing.
HCI (8) 2007: 705-714 |
| 93 | EE | Keisuke Yamazaki,
Motoaki Kawanabe,
Sumio Watanabe,
Masashi Sugiyama,
Klaus-Robert Müller:
Asymptotic Bayesian generalization error when training and test distributions are different.
ICML 2007: 1079-1086 |
| 92 | EE | Shigeyuki Oba,
Motoaki Kawanabe,
Klaus-Robert Müller,
Shin Ishii:
Heterogeneous Component Analysis.
NIPS 2007 |
| 91 | EE | Benjamin Blankertz,
Motoaki Kawanabe,
Ryota Tomioka,
Friederike Hohlefeld,
Vadim V. Nikulin,
Klaus-Robert Müller:
Invariant Common Spatial Patterns: Alleviating Nonstationarities in Brain-Computer Interfacing.
NIPS 2007 |
| 90 | EE | Roman Krepki,
Gabriel Curio,
Benjamin Blankertz,
Klaus-Robert Müller:
Berlin Brain-Computer Interface - The HCI communication channel for discovery.
Int. J. Hum.-Comput. Stud. 65(5): 460-477 (2007) |
| 89 | EE | Gilles Blanchard,
Christin Schäfer,
Yves Rozenholc,
Klaus-Robert Müller:
Optimal dyadic decision trees.
Machine Learning 66(2-3): 209-241 (2007) |
| 88 | EE | Roman Krepki,
Benjamin Blankertz,
Gabriel Curio,
Klaus-Robert Müller:
The Berlin Brain-Computer Interface (BBCI) - towards a new communication channel for online control in gaming applications.
Multimedia Tools Appl. 33(1): 73-90 (2007) |
| 2006 |
|---|
| 87 | | Katrin Franke,
Klaus-Robert Müller,
Bertram Nickolay,
Ralf Schäfer:
Pattern Recognition, 28th DAGM Symposium, Berlin, Germany, September 12-14, 2006, Proceedings
Springer 2006 |
| 86 | EE | Masashi Sugiyama,
Benjamin Blankertz,
Matthias Krauledat,
Guido Dornhege,
Klaus-Robert Müller:
Importance-Weighted Cross-Validation for Covariate Shift.
DAGM-Symposium 2006: 354-363 |
| 85 | EE | Konrad Rieck,
Pavel Laskov,
Klaus-Robert Müller:
Efficient Algorithms for Similarity Measures over Sequential Data: A Look Beyond Kernels.
DAGM-Symposium 2006: 374-383 |
| 84 | EE | Ryota Tomioka,
Guido Dornhege,
Guido Nolte,
Kazuyuki Aihara,
Klaus-Robert Müller:
Optimizing Spectral Filters for Single Trial EEG Classification.
DAGM-Symposium 2006: 414-423 |
| 83 | EE | Motoaki Kawanabe,
Gilles Blanchard,
Masashi Sugiyama,
Vladimir Spokoiny,
Klaus-Robert Müller:
A Novel Dimension Reduction Procedure for Searching Non-Gaussian Subspaces.
ICA 2006: 149-156 |
| 82 | EE | Keisuke Yamazaki,
Kenji Nagata,
Sumio Watanabe,
Klaus-Robert Müller:
A Model Selection Method Based on Bound of Learning Coefficient.
ICANN (2) 2006: 371-380 |
| 81 | EE | Ryota Tomioka,
Kazuyuki Aihara,
Klaus-Robert Müller:
Logistic Regression for Single Trial EEG Classification.
NIPS 2006: 1377-1384 |
| 80 | EE | Mikio L. Braun,
Joachim M. Buhmann,
Klaus-Robert Müller:
Denoising and Dimension Reduction in Feature Space.
NIPS 2006: 185-192 |
| 79 | EE | Matthias Krauledat,
Michael Schröder,
Benjamin Blankertz,
Klaus-Robert Müller:
Reducing Calibration Time For Brain-Computer Interfaces: A Clustering Approach.
NIPS 2006: 753-760 |
| 78 | EE | Julian Laub,
Jakob Macke,
Klaus-Robert Müller,
Felix A. Wichmann:
Inducing Metric Violations in Human Similarity Judgements.
NIPS 2006: 777-784 |
| 77 | EE | Benjamin Blankertz,
Guido Dornhege,
Steven Lemm,
Matthias Krauledat,
Gabriel Curio,
Klaus-Robert Müller:
The Berlin Brain-Computer Interface: Machine Learning Based Detection of User Specific Brain States.
J. UCS 12(6): 581-607 (2006) |
| 76 | EE | Pavel Laskov,
Christian Gehl,
Stefan Krüger,
Klaus-Robert Müller:
Incremental Support Vector Learning: Analysis, Implementation and Applications.
Journal of Machine Learning Research 7: 1909-1936 (2006) |
| 75 | EE | Gilles Blanchard,
Motoaki Kawanabe,
Masashi Sugiyama,
Vladimir Spokoiny,
Klaus-Robert Müller:
In Search of Non-Gaussian Components of a High-Dimensional Distribution.
Journal of Machine Learning Research 7: 247-282 (2006) |
| 74 | EE | Stefan Harmeling,
Guido Dornhege,
David M. J. Tax,
Frank C. Meinecke,
Klaus-Robert Müller:
From outliers to prototypes: Ordering data.
Neurocomputing 69(13-15): 1608-1618 (2006) |
| 73 | EE | Julian Laub,
Volker Roth,
Joachim M. Buhmann,
Klaus-Robert Müller:
On the information and representation of non-Euclidean pairwise data.
Pattern Recognition 39(10): 1815-1826 (2006) |
| 2005 |
|---|
| 72 | EE | Masashi Sugiyama,
Klaus-Robert Müller:
Model Selection Under Covariate Shift.
ICANN (2) 2005: 235-240 |
| 71 | EE | Guido Nolte,
Andreas Ziehe,
Frank C. Meinecke,
Klaus-Robert Müller:
Analyzing Coupled Brain Sources: Distinguishing True from Spurious Interaction.
NIPS 2005 |
| 70 | EE | Gilles Blanchard,
Masashi Sugiyama,
Motoaki Kawanabe,
Vladimir Spokoiny,
Klaus-Robert Müller:
Non-Gaussian Component Analysis: a Semi-parametric Framework for Linear Dimension Reduction.
NIPS 2005 |
| 69 | EE | Guido Dornhege,
Benjamin Blankertz,
Matthias Krauledat,
Florian Losch,
Gabriel Curio,
Klaus-Robert Müller:
Optimizing spatio-temporal filters for improving Brain-Computer Interfacing.
NIPS 2005 |
| 68 | | Pavel Laskov,
Konrad Rieck,
Christin Schäfer,
Klaus-Robert Müller:
Visualization of anomaly detection using prediction sensitivity.
Sicherheit 2005: 197-208 |
| 67 | EE | Klaus-Robert Müller,
Gunnar Rätsch,
Sören Sonnenburg,
Sebastian Mika,
Michael Grimm,
Nikolaus Heinrich:
Classifying 'Drug-likeness' with Kernel-Based Learning Methods.
Journal of Chemical Information and Modeling 45(2): 249-253 (2005) |
| 66 | EE | Motoaki Kawanabe,
Klaus-Robert Müller:
Estimating Functions for Blind Separation When Sources Have Variance Dependencies.
Journal of Machine Learning Research 6: 453-482 (2005) |
| 2004 |
|---|
| 65 | EE | Masashi Sugiyama,
Motoaki Kawanabe,
Klaus-Robert Müller:
Regularizing generalization error estimators: a novel approach to robust model selection.
ESANN 2004: 163-168 |
| 64 | EE | Motoaki Kawanabe,
Klaus-Robert Müller:
Estimating Functions for Blind Separation when Sources Have Variance-Dependencies.
ICA 2004: 136-143 |
| 63 | EE | Frank C. Meinecke,
Stefan Harmeling,
Klaus-Robert Müller:
Robust ICA for Super-Gaussian Sources.
ICA 2004: 217-224 |
| 62 | EE | Arie Yeredor,
Andreas Ziehe,
Klaus-Robert Müller:
Approximate Joint Diagonalization Using a Natural Gradient Approach.
ICA 2004: 89-96 |
| 61 | EE | David M. J. Tax,
Klaus-Robert Müller:
A Consistency-Based Model Selection for One-Class Classification.
ICPR (3) 2004: 363-366 |
| 60 | EE | Klaus-Robert Müller,
Ricardo Vigário,
Frank C. Meinecke,
Andreas Ziehe:
Blind Source Separation Techniques for Decomposing Event-Related Brain Signals.
I. J. Bifurcation and Chaos 14(2): 773-791 (2004) |
| 59 | EE | Andreas Ziehe,
Pavel Laskov,
Guido Nolte,
Klaus-Robert Müller:
A Fast Algorithm for Joint Diagonalization with Non-orthogonal Transformations and its Application to Blind Source Separation.
Journal of Machine Learning Research 5: 777-800 (2004) |
| 58 | EE | Julian Laub,
Klaus-Robert Müller:
Feature Discovery in Non-Metric Pairwise Data.
Journal of Machine Learning Research 5: 801-818 (2004) |
| 57 | EE | Koji Tsuda,
Shotaro Akaho,
Motoaki Kawanabe,
Klaus-Robert Müller:
Asymptotic Properties of the Fisher Kernel.
Neural Computation 16(1): 115-137 (2004) |
| 56 | EE | Masashi Sugiyama,
Motoaki Kawanabe,
Klaus-Robert Müller:
Trading Variance Reduction with Unbiasedness: The Regularized Subspace Information Criterion for Robust Model Selection in Kernel Regression.
Neural Computation 16(5): 1077-1104 (2004) |
| 55 | EE | Stefan Harmeling,
Frank C. Meinecke,
Klaus-Robert Müller:
Injecting noise for analysing the stability of ICA components.
Signal Processing 84(2): 255-266 (2004) |
| 2003 |
|---|
| 54 | EE | David M. J. Tax,
Klaus-Robert Müller:
Feature Extraction for One-Class Classification.
ICANN 2003: 342-349 |
| 53 | EE | Guido Dornhege,
Benjamin Blankertz,
Gabriel Curio,
Klaus-Robert Müller:
Increase Information Transfer Rates in BCI by CSP Extension to Multi-class.
NIPS 2003 |
| 52 | EE | Sebastian Mika,
Gunnar Rätsch,
Jason Weston,
Bernhard Schölkopf,
Alex J. Smola,
Klaus-Robert Müller:
Constructing Descriptive and Discriminative Nonlinear Features: Rayleigh Coefficients in Kernel Feature Spaces.
IEEE Trans. Pattern Anal. Mach. Intell. 25(5): 623-633 (2003) |
| 51 | EE | Andreas Ziehe,
Motoaki Kawanabe,
Stefan Harmeling,
Klaus-Robert Müller:
Blind Separation of Post-nonlinear Mixtures using Linearizing Transformations and Temporal Decorrelation.
Journal of Machine Learning Research 4: 1319-1338 (2003) |
| 50 | EE | Stefan Harmeling,
Andreas Ziehe,
Motoaki Kawanabe,
Klaus-Robert Müller:
Kernel-Based Nonlinear Blind Source Separation.
Neural Computation 15(5): 1089-1124 (2003) |
| 2002 |
|---|
| 49 | EE | Sören Sonnenburg,
Gunnar Rätsch,
Arun K. Jagota,
Klaus-Robert Müller:
New Methods for Splice Site Recognition.
ICANN 2002: 329-336 |
| 48 | EE | Masashi Sugiyama,
Klaus-Robert Müller:
Selecting Ridge Parameters in Infinite Dimensional Hypothesis Spaces.
ICANN 2002: 528-534 |
| 47 | EE | Guido Dornhege,
Benjamin Blankertz,
Gabriel Curio,
Klaus-Robert Müller:
Combining Features for BCI.
NIPS 2002: 1115-1122 |
| 46 | EE | Koji Tsuda,
Motoaki Kawanabe,
Klaus-Robert Müller:
Clustering with the Fisher Score.
NIPS 2002: 729-736 |
| 45 | EE | Volker Roth,
Julian Laub,
Joachim M. Buhmann,
Klaus-Robert Müller:
Going Metric: Denoising Pairwise Data.
NIPS 2002: 817-824 |
| 44 | EE | Gunnar Rätsch,
Sebastian Mika,
Bernhard Schölkopf,
Klaus-Robert Müller:
Constructing Boosting Algorithms from SVMs: An Application to One-Class Classification.
IEEE Trans. Pattern Anal. Mach. Intell. 24(9): 1184-1199 (2002) |
| 43 | EE | Masashi Sugiyama,
Klaus-Robert Müller:
The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces.
Journal of Machine Learning Research 3: 323-359 (2002) |
| 42 | EE | Koji Tsuda,
Motoaki Kawanabe,
Gunnar Rätsch,
Sören Sonnenburg,
Klaus-Robert Müller:
A New Discriminative Kernel from Probabilistic Models.
Neural Computation 14(10): 2397-2414 (2002) |
| 41 | EE | Noboru Murata,
Motoaki Kawanabe,
Andreas Ziehe,
Klaus-Robert Müller,
Shun-ichi Amari:
On-line learning in changing environments with applications in supervised and unsupervised learning.
Neural Networks 15(4-6): 743-760 (2002) |
| 2001 |
|---|
| 40 | EE | Koji Tsuda,
Gunnar Rätsch,
Sebastian Mika,
Klaus-Robert Müller:
Learning to Predict the Leave-One-Out Error of Kernel Based Classifiers.
ICANN 2001: 331-338 |
| 39 | EE | Frank C. Meinecke,
Andreas Ziehe,
Motoaki Kawanabe,
Klaus-Robert Müller:
Estimating the Reliability of ICA Projections.
NIPS 2001: 1181-1188 |
| 38 | EE | Benjamin Blankertz,
Gabriel Curio,
Klaus-Robert Müller:
Classifying Single Trial EEG: Towards Brain Computer Interfacing.
NIPS 2001: 157-164 |
| 37 | EE | Stefan Harmeling,
Alexander Ziehe,
Motoaki Kawanabe,
Klaus-Robert Müller:
Kernel Feature Spaces and Nonlinear Blind Souce Separation.
NIPS 2001: 761-768 |
| 36 | EE | Koji Tsuda,
Motoaki Kawanabe,
Gunnar Rätsch,
Sören Sonnenburg,
Klaus-Robert Müller:
A New Discriminative Kernel From Probabilistic Models.
NIPS 2001: 977-984 |
| 35 | | Gunnar Rätsch,
Takashi Onoda,
Klaus-Robert Müller:
Soft Margins for AdaBoost.
Machine Learning 42(3): 287-320 (2001) |
| 2000 |
|---|
| 34 | | Sara A. Solla,
Todd K. Leen,
Klaus-Robert Müller:
Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29 - December 4, 1999]
The MIT Press 2000 |
| 33 | | Gunnar Rätsch,
Manfred K. Warmuth,
Sebastian Mika,
Takashi Onoda,
Steven Lemm,
Klaus-Robert Müller:
Barrier Boosting.
COLT 2000: 170-179 |
| 32 | | Sebastian Mika,
Gunnar Rätsch,
Klaus-Robert Müller:
A Mathematical Programming Approach to the Kernel Fisher Algorithm.
NIPS 2000: 591-597 |
| 31 | | Gunnar Rätsch,
Bernhard Schölkopf,
Alex J. Smola,
Sebastian Mika,
Takashi Onoda,
Klaus-Robert Müller:
Robust Ensemble Learning for Data Mining.
PAKDD 2000: 341-344 |
| 30 | | Alexander Zien,
Gunnar Rätsch,
Sebastian Mika,
Bernhard Schölkopf,
Thomas Lengauer,
Klaus-Robert Müller:
Engineering support vector machine kernels that recognize translation initiation sites.
Bioinformatics 16(9): 799-807 (2000) |
| 1999 |
|---|
| 29 | EE | Stefan Liehr,
Klaus Pawelzik,
Jens Kohlmorgen,
Steven Lemm,
Klaus-Robert Müller:
Hidden Markov gating for prediction of change points in switching dynamical systems.
ESANN 1999: 405-410 |
| 28 | | Alexander Zien,
Gunnar Rätsch,
Sebastian Mika,
Bernhard Schölkopf,
Christian Lemmen,
Alex J. Smola,
Thomas Lengauer,
Klaus-Robert Müller:
Engineering Support Vector Machine Kerneis That Recognize Translation Initialion Sites.
German Conference on Bioinformatics 1999: 37-43 |
| 27 | EE | Sebastian Mika,
Gunnar Rätsch,
Jason Weston,
Bernhard Schölkopf,
Alex J. Smola,
Klaus-Robert Müller:
Invariant Feature Extraction and Classification in Kernel Spaces.
NIPS 1999: 526-532 |
| 26 | EE | Gunnar Rätsch,
Bernhard Schölkopf,
Alex J. Smola,
Klaus-Robert Müller,
Takashi Onoda,
Sebastian Mika:
v-Arc: Ensemble Learning in the Presence of Outliers.
NIPS 1999: 561-567 |
| 25 | EE | Lucas C. Parra,
Clay Spence,
Paul Sajda,
Andreas Ziehe,
Klaus-Robert Müller:
Unmixing Hyperspectral Data.
NIPS 1999: 942-948 |
| 24 | EE | Bernhard Schölkopf,
Sebastian Mika,
Christopher J. C. Burges,
Phil Knirsch,
Klaus-Robert Müller,
Gunnar Rätsch,
Alexander J. Smola:
Input space versus feature space in kernel-based methods.
IEEE Transactions on Neural Networks 10(5): 1000-1017 (1999) |
| 23 | EE | Bernhard Schölkopf,
Klaus-Robert Müller,
Alex J. Smola:
Lernen mit Kernen: Support-Vektor-Methoden zur Analyse hochdimensionaler Daten.
Inform., Forsch. Entwickl. 14(3): 154-163 (1999) |
| 1998 |
|---|
| 22 | | Genevieve B. Orr,
Klaus-Robert Müller:
Neural Networks: Tricks of the Trade, this book is an outgrowth of a 1996 NIPS workshop
Springer 1998 |
| 21 | | Gunnar Rätsch,
Takashi Onoda,
Klaus-Robert Müller:
An Improvement of AdaBoost to Avoid Overfitting.
ICONIP 1998: 506-509 |
| 20 | EE | Sebastian Mika,
Bernhard Schölkopf,
Alex J. Smola,
Klaus-Robert Müller,
Matthias Scholz,
Gunnar Rätsch:
Kernel PCA and De-Noising in Feature Spaces.
NIPS 1998: 536-542 |
| 19 | EE | Gunnar Rätsch,
Takashi Onoda,
Klaus-Robert Müller:
Regularizing AdaBoost.
NIPS 1998: 564-570 |
| 18 | | Bernhard Schölkopf,
Alex J. Smola,
Klaus-Robert Müller:
Nonlinear Component Analysis as a Kernel Eigenvalue Problem.
Neural Computation 10(5): 1299-1319 (1998) |
| 17 | EE | Alex J. Smola,
Bernhard Schölkopf,
Klaus-Robert Müller:
The connection between regularization operators and support vector kernels.
Neural Networks 11(4): 637-649 (1998) |
| 16 | | Jens Kohlmorgen,
Klaus-Robert Müller:
Data Set A is a Pattern Matching Problem.
Neural Processing Letters 7(1): 43-47 (1998) |
| 1997 |
|---|
| 15 | | Jens Kohlmorgen,
Klaus-Robert Müller,
J. Rittweger,
Klaus Pawelzik:
Analysis of Wake/Sleep EEG with Competing Experts.
ICANN 1997: 1077-1082 |
| 14 | | Bernhard Schölkopf,
Alex J. Smola,
Klaus-Robert Müller:
Kernel Principal Component Analysis.
ICANN 1997: 583-588 |
| 13 | | Klaus-Robert Müller,
Alex J. Smola,
Gunnar Rätsch,
Bernhard Schölkopf,
Jens Kohlmorgen,
Vladimir Vapnik:
Predicting Time Series with Support Vector Machines.
ICANN 1997: 999-1004 |
| 12 | | Jens Kohlmorgen,
Klaus-Robert Müller,
Klaus Pawelzik:
Analysis of Drifting Dynamics with Neural Network Hidden Markov Models.
NIPS 1997 |
| 1996 |
|---|
| 11 | | Klaus Pawelzik,
Klaus-Robert Müller,
Jens Kohlmorgen:
Prediction of Mixtures.
ICANN 1996: 127-132 |
| 10 | | Jens Kohlmorgen,
Klaus-Robert Müller,
Klaus Pawelzik:
Analysis of Drifting Dynamics with Competing Predictors.
ICANN 1996: 785-790 |
| 9 | EE | Noboru Murata,
Klaus-Robert Müller,
Andreas Ziehe,
Shun-ichi Amari:
Adaptive On-line Learning in Changing Environments.
NIPS 1996: 599-605 |
| 8 | EE | Genevieve B. Orr,
Klaus-Robert Müller:
Introduction.
Neural Networks: Tricks of the Trade 1996: 1-5 |
| 7 | EE | Genevieve B. Orr,
Klaus-Robert Müller:
Improving Network Models and Algorithmic Tricks: Preface.
Neural Networks: Tricks of the Trade 1996: 141-144 |
| 6 | EE | Genevieve B. Orr,
Klaus-Robert Müller:
Representing and Incorporating Prior Knowledge in Neural Network Training: Preface.
Neural Networks: Tricks of the Trade 1996: 235-238 |
| 5 | EE | Genevieve B. Orr,
Klaus-Robert Müller:
Tricks for Time Series: Preface.
Neural Networks: Tricks of the Trade 1996: 343-346 |
| 4 | EE | Genevieve B. Orr,
Klaus-Robert Müller:
Regularization Techniques to Improve Generalization: Preface.
Neural Networks: Tricks of the Trade 1996: 51-54 |
| 3 | EE | Genevieve B. Orr,
Klaus-Robert Müller:
Speeding Learning: Preface.
Neural Networks: Tricks of the Trade 1996: 7-8 |
| 2 | EE | Yann LeCun,
Léon Bottou,
Genevieve B. Orr,
Klaus-Robert Müller:
Effiicient BackProp.
Neural Networks: Tricks of the Trade 1996: 9-50 |
| 1995 |
|---|
| 1 | EE | Shun-ichi Amari,
Noboru Murata,
Klaus-Robert Müller,
M. Finke,
Howard Hua Yang:
Statistical Theory of Overtraining - Is Cross-Validation Asymptotically Effective?
NIPS 1995: 176-182 |
