|
| The series contains reviewed reports on Machine Learning (Machine Learning Reports) [MLR] (citation see bottom) |
| This webpage is the platform to access these reports. In case of any questions contact the Editors (see above). |
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2007 |
|
| Report 01:Preprocessing of Nuclear Magnetic Resonance Spectrometry Data |
| Report 02:Aggregation of multiple peaklists by use of an improved Neural Gas Network |
| Report 03:Sobolev Metrics for Learning of Functional Data - Mathematical and Theoretical Aspects |
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2008 |
|
| Report 01:Combining Phenotypic and Genotypic Learning |
| Report 02:Regularization in Matrix Relevance Learning |
| Report 03:Discriminative Visualization by Limited Rank Matrix Learning |
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2009 |
|
| Report 01:Stationarity of Matrix Relevance Learning Vector Quantization |
| Report 02:Extending RSLVQ to handle data points with uncertain class assignments |
| Report 03:Mathematical Aspects of Divergence Based Vector Quantization Using Frechet-Derivatives |
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2010 |
|
| Report 01:Mathematical Aspects of Divergence Based Vector Quantization Using Frechet-Derivatives - Extended and revised version |
| Report 02:Mathematical Foundations of the Generalization of t-SNE and SNE for Arbitrary Divergences |
| Report 03:Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization |
| Report 04:Proceedings of the Workshop - New Challenges in Neural Computation 2010 |
| Report 05:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2010 |
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2011 |
|
| Report 01:Proceedings of the German-Polish Workshop on Computational Biology, Scheduling and Machine Learning (ICOLE'2010) |
| Report 02:Fuzzy Supervised Neural Gas for Semi-supervised Vector Quantization -- Theoretical Aspects |
| Report 03:About Sparsity in Functional Relevance Learning in Generalized Learning Vector Quantization |
| Report 04:Classification of Hyperspectral Imagery with Neural Networks: Comparison to Conventional Tools |
| Report 05:Proceedings of the Workshop - New Challenges in Neural Computation 2011 |
| Report 06:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2011 |
| Report 07:Derivation of a Generalized Conn-Index for Fuzzy Clustering Validation |
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2012 |
|
| Report 01:Proceedings of the German-Polish Workshop on Computational Biology, Scheduling and Machine Learning (ICOLE'2011) |
| Report 02:A Note on Gradient Based Learning in Vector Quantization Using Differentiable Kernels for Hilbert and Banach Spaces |
| Report 03:Proceedings of the Workshop - New Challenges in Neural Computation 2012 |
| Report 04:Data analysis of (non-)metric (dis-)similarities at linear costs (This approach has been published in a Simbad 2013 paper) |
| Report 05:SOM-based topology visualization for interactive analysis of high-dimensional large datasets |
| Report 06:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2012 |
|
2013 |
| Report 01:Detection of Targets in Characteristic GPR Sensor Data Using Machine Learning Techniques |
| Report 02:Workshop New Challenges in Neural Computation 2013 |
| Report 03:Large scale Nyström approximation for non-metric similarity and dissimilarity data |
| Report 04:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2013 |
| Report 05:Analysis of temporal Kinect motion capturing data |
| Report 06:About Learning of Supervised Generative Models for Dissimilarity Data |
|
2014 |
| Report 01:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2014 |
| Report 02:Workshop New Challenges in Neural Computation 2014 |
| Report 03:Median Variants of LVQ for Optimization of Statistical Quality Measures for Classification of Dissimilarity Data |
|
2015 |
| Report 01:An Application of the Generalized Matrix Learning Vector Quantization Method for Cut-off-line Classification of Automobile-Headlights |
| Report 02:A Comment on the Functional L_p^{TS} -Measure Regarding the Norm Properties |
| Report 03:Workshop New Challenges in Neural Computation 2015 |
| Report 04:Proceedings of ICOLE Workshop - 2015 |
|
2016 |
| Report 01:A Probabilistic Classifier Model with Adaptive Rejection Option |
| Report 02:n.a. |
| Report 03:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2016 |
| Report 04:Workshop New Challenges in Neural Computation 2016 |
|
|
2017 |
| Report 01:Restricted Tangent Distances for Local Data Dissimilarities |
| Report 02:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2017 |
| Report 03:Workshop New Challenges in Neural Computation 2017 |
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2018 |
| Report 01:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2018 |
| Report 02:Learning Vector Quantization Capsules |
|
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2019 |
| Report 01:Supervised Learning - An Introduction |
| Report 02:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2019 |
|
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2020 |
| Report 01:Analysemethoden zur Abschätzung
von Belastungsintensitäten bei
Kniebeugen unter Verwendung
interpretierbarer Modelle der
Künstlichen Intelligenz |
| Report 02:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2020 |
|
|
2021 |
| Report 01:New Variants of the Counter
Propagation Network for
Classification Learning -- A Formal
Description of Strategies and
Respective Approaches -- |
| Report 02:The Resolved Mutual Information
Function for Characterization of
Spatial Correlations in Sequences and
Labeled Graphs |
| Report 03:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2021 |
|
|
|
2022 |
| Report 01:The Resolved Mutual Information Function for
Fingerprinting Biochemical Compounds Based on
their Structural Formulas |
| Report 02:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2022 |
|
|
|
2023 |
| Report 01:Regression Neural Gas: Extension of Standard Neural Gas and its application for function approximation |
| Report 02:Extending the concept of soft sensors
to green sensing |
| Report 03:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2023 |
|
|
|
2024 |
| Report 01:Proceedings of the Mittweida Workshop on Computational Intelligence - MIWOCI 2024 |
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Citation please as: e.g.
@PROCEEDINGS{MLR0107,
editor = "Thomas Villmann and Frank-Michael Schleif",
title = "Machine Learning Reports 01/2007",
series = "Machine Learning Reports",
year = {2007},
volume = {1},
number = {MLR-01-2007},
note = "ISSN:1865-3960 http://www.techfak.uni-bielefeld.de/$\tilde{ }$fschleif/mlr/mlr\_01\_2007.pdf",
}
@inproceedings{MLR0107/Schleif2007a,
author = {F.-M. Schleif},
title = {Preprocessing of Nuclear Magnetic Resonance Spectrometry Data},
booktitle = {Machine Learning Reports 01/2007}
year = {2007},
pages = {XX-YY},
note = "ISSN:1865-3960 http://www.techfak.uni-bielefeld.de/$\tilde{ }$fschleif/mlr/mlr\_01\_2007.pdf",
crossref = {MLR0107}
}
|
| stylesheet: style files (LaTeX) |