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ORCIDMikio L. Braun
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- affiliation: TU Berlin, Machine Learning Group, Germany
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2020 – today
- 2021
[c17]Mikio Ludwig Braun, Tim P. Vogels:
Online Learning Of Neural Computations From Sparse Temporal Feedback. NeurIPS 2021: 16437-16450
2010 – 2019
- 2017
- [j10]Alexander Bauer, Mikio L. Braun, Klaus-Robert Müller
:
Accurate Maximum-Margin Training for Parsing With Context-Free Grammars. IEEE Trans. Neural Networks Learn. Syst. 28(1): 44-56 (2017) - 2016
- [i3]Ivana Balazevic, Mikio Ludwig Braun, Klaus-Robert Müller:
Language Detection For Short Text Messages In Social Media. CoRR abs/1608.08515 (2016) - 2015
- [j9]Tammo Krueger, Danny Panknin, Mikio L. Braun:
Fast cross-validation via sequential testing. J. Mach. Learn. Res. 16: 1103-1155 (2015) - [j8]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller:
Extracting latent brain states - Towards true labels in cognitive neuroscience experiments. NeuroImage 120: 225-253 (2015) - [c16]Nico Görnitz, Mikio L. Braun, Marius Kloft:
Hidden Markov Anomaly Detection. ICML 2015: 1833-1842 - 2014
- [c15]Nico Görnitz, Anne Porbadnigk, Alexander Binder, Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller, Marius Kloft:
Learning and Evaluation in Presence of Non-i.i.d. Label Noise. AISTATS 2014: 293-302 - [c14]Anne K. Porbadnigk, Nico Görnitz, Claudia Sannelli, Alexander Binder, Mikio L. Braun, Marius Kloft, Klaus-Robert Müller:
When brain and behavior disagree: Tackling systematic label noise in EEG data with machine learning. BCI 2014: 1-4 - [i2]Joaquin Vanschoren, Mikio L. Braun, Cheng Soon Ong:
Open science in machine learning. CoRR abs/1402.6013 (2014) - 2013
- [j7]Grégoire Montavon, Mikio L. Braun, Tammo Krueger, Klaus-Robert Müller:
Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment. IEEE Signal Process. Mag. 30(4): 62-74 (2013) - 2012
- [c13]Felix Bießmann, Jens-Michalis Papaioannou, Mikio L. Braun, Andreas Harth:
Canonical Trends: Detecting Trend Setters in Web Data. ICML 2012 - [c12]Felix Bießmann, Jens-Michalis Papaioannou, Andreas Harth, M. L. Jugel, Klaus-Robert Müller, Mikio L. Braun:
Quantifying spatiotemporal dynamics of twitter replies to news feeds. MLSP 2012: 1-6 - [c11]Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller:
Deep Boltzmann Machines as Feed-Forward Hierarchies. AISTATS 2012: 798-804 - [i1]Tammo Krueger, Danny Panknin, Mikio L. Braun:
Fast Cross-Validation via Sequential Testing. CoRR abs/1206.2248 (2012) - 2011
- [j6]Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller:
Kernel Analysis of Deep Networks. J. Mach. Learn. Res. 12: 2563-2581 (2011) - 2010
- [c10]Grégoire Montavon, Mikio L. Braun, Klaus-Robert Müller:
Layer-wise analysis of deep networks with Gaussian kernels. NIPS 2010: 1678-1686
2000 – 2009
- 2009
- [j5]Claudia Sannelli, Mikio L. Braun, Klaus-Robert Müller:
Improving BCI performance by task-related trial pruning. Neural Networks 22(9): 1295-1304 (2009) - [c9]Nicole Krämer, Masashi Sugiyama, Mikio L. Braun:
Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression. AISTATS 2009: 288-295 - 2008
- [j4]Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller:
On Relevant Dimensions in Kernel Feature Spaces. J. Mach. Learn. Res. 9: 1875-1908 (2008) - 2007
- [j3]Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Léon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander J. Smola, Pascal Vincent, Jason Weston, Robert C. Williamson:
The Need for Open Source Software in Machine Learning. J. Mach. Learn. Res. 8: 2443-2466 (2007) - [c8]Nicole Krämer, Mikio L. Braun:
Kernelizing PLS, degrees of freedom, and efficient model selection. ICML 2007: 441-448 - 2006
- [j2]Mikio L. Braun:
Accurate Error Bounds for the Eigenvalues of the Kernel Matrix. J. Mach. Learn. Res. 7: 2303-2328 (2006) - [c7]Mikio L. Braun, Tilman Lange, Joachim M. Buhmann:
Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information. DAGM-Symposium 2006: 344-353 - [c6]Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert Müller:
Denoising and Dimension Reduction in Feature Space. NIPS 2006: 185-192 - 2005
- [b1]Mikio Ludwig Braun:
Spectral properties of the kernel matrix and their relation to kernel methods in machine learning. University of Bonn, Germany, 2005, pp. 1-153 - 2004
- [j1]Tilman Lange, Volker Roth, Mikio L. Braun, Joachim M. Buhmann:
Stability-Based Validation of Clustering Solutions. Neural Comput. 16(6): 1299-1323 (2004) - 2002
- [c5]Volker Roth, Tilman Lange, Mikio L. Braun, Joachim M. Buhmann:
A Resampling Approach to Cluster Validation. COMPSTAT 2002: 123-128 - [c4]Volker Roth, Mikio L. Braun, Tilman Lange, Joachim M. Buhmann:
Stability-Based Model Order Selection in Clustering with Applications to Gene Expression Data. ICANN 2002: 607-612 - [c3]Tilman Lange, Mikio L. Braun, Volker Roth, Joachim M. Buhmann:
Stability-Based Model Selection. NIPS 2002: 617-624 - 2001
- [c2]Mikio L. Braun, Joachim M. Buhmann:
The Noisy Euclidean Traveling Salesman Problem and Learning. NIPS 2001: 351-358
1990 – 1999
- 1998
- [c1]Michael Becker, Mikio L. Braun, Rolf Eckmiller:
Retina implant adjustment with reinforcement learning. ICASSP 1998: 1181-1184
Coauthor Index
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