Mikio L. Braun

According to our database1, Mikio L. Braun authored at least 25 papers between 1998 and 2017.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

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Bibliography

2017
Accurate Maximum-Margin Training for Parsing With Context-Free Grammars.
IEEE Trans. Neural Netw. Learning Syst., 2017

2015
Extracting latent brain states - Towards true labels in cognitive neuroscience experiments.
NeuroImage, 2015

Fast cross-validation via sequential testing.
J. Mach. Learn. Res., 2015

Hidden Markov Anomaly Detection.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Learning and Evaluation in Presence of Non-i.i.d. Label Noise.
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013
Analyzing Local Structure in Kernel-Based Learning: Explanation, Complexity, and Reliability Assessment.
IEEE Signal Process. Mag., 2013

2012
Deep Boltzmann Machines as Feed-Forward Hierarchies.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Quantifying spatiotemporal dynamics of twitter replies to news feeds.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012

Canonical Trends: Detecting Trend Setters in Web Data.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Kernel Analysis of Deep Networks.
J. Mach. Learn. Res., 2011

2010
Layer-wise analysis of deep networks with Gaussian kernels.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Improving BCI performance by task-related trial pruning.
Neural Networks, 2009

Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

2008
On Relevant Dimensions in Kernel Feature Spaces.
J. Mach. Learn. Res., 2008

2007
The Need for Open Source Software in Machine Learning.
J. Mach. Learn. Res., 2007

Kernelizing PLS, degrees of freedom, and efficient model selection.
Proceedings of the Machine Learning, 2007

2006
Accurate Error Bounds for the Eigenvalues of the Kernel Matrix.
J. Mach. Learn. Res., 2006

Denoising and Dimension Reduction in Feature Space.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Model Selection in Kernel Methods Based on a Spectral Analysis of Label Information.
Proceedings of the Pattern Recognition, 2006

2005
Spectral properties of the kernel matrix and their relation to kernel methods in machine learning.
PhD thesis, 2005

2004
Stability-Based Validation of Clustering Solutions.
Neural Computation, 2004

2002
Stability-Based Model Selection.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Stability-Based Model Order Selection in Clustering with Applications to Gene Expression Data.
Proceedings of the Artificial Neural Networks, 2002

2001
The Noisy Euclidean Traveling Salesman Problem and Learning.
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001

1998
Retina implant adjustment with reinforcement learning.
Proceedings of the 1998 IEEE International Conference on Acoustics, 1998


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