Marika Kaden

Orcid: 0000-0002-2849-3463

Affiliations:
  • University of Applied Sciences Mittweida, Mittweida, Germany


According to our database1, Marika Kaden authored at least 74 papers between 2011 and 2024.

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

Timeline

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Bibliography

2024
Biologically-Informed Shallow Classification Learning Integrating Pathway Knowledge.
Proceedings of the 17th International Joint Conference on Biomedical Engineering Systems and Technologies, 2024

2023
Multi-proximity based embedding scheme for learning vector quantization-based classification of biochemical structured data.
Neurocomputing, October, 2023

Alignment-Free Sequence Comparison: A Systematic Survey From a Machine Learning Perspective.
IEEE ACM Trans. Comput. Biol. Bioinform., 2023

Compression of Particle Images for Inspection of Microgravity Experiments by Means of a Symmetric Structural Auto-Encoder.
Proceedings of the 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2023

A White-Box Workflow for the Prediction of Food Content From Near-Infrared Data Based on Fourier-Transformation.
Proceedings of the 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing, 2023

Variants of Neural Gas for Regression Learning.
Proceedings of the 31st European Symposium on Artificial Neural Networks, 2023

Efficient Representation of Biochemical Structures for Supervised and Unsupervised Machine Learning Models Using Multi-Sensoric Embeddings.
Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023

2022
Quantum-inspired learning vector quantizers for prototype-based classification.
Neural Comput. Appl., 2022

Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences.
Neural Comput. Appl., 2022

Variants of recurrent learning vector quantization.
Neurocomputing, 2022

Prototype-based One-Class-Classification Learning Using Local Representations.
Proceedings of the International Joint Conference on Neural Networks, 2022

A Learning Vector Quantization Architecture for Transfer Learning Based Classification in Case of Multiple Sources by Means of Null-Space Evaluation.
Proceedings of the Advances in Intelligent Data Analysis XX, 2022

Trustworthiness and Confidence of Gait Phase Predictions in Changing Environments Using Interpretable Classifier Models.
Proceedings of the Neural Information Processing - 29th International Conference, 2022

Efficient classification learning of biochemical structured data by means of relevance weighting for sensoric response features.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021
AI-Based Multi Sensor Fusion for Smart Decision Making: A Bi-Functional System for Single Sensor Evaluation in a Classification Task.
Sensors, 2021

The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers.
Entropy, 2021

Sensors data fusion for smart decisions making: A novel bi-functional system for the evaluation of sensors contribution in classification problems.
Proceedings of the 22nd IEEE International Conference on Industrial Technology, 2021

Possibilistic Classification Learning Based on Contrastive Loss in Learning Vector Quantizer Networks.
Proceedings of the Artificial Intelligence and Soft Computing, 2021

RecLVQ: Recurrent Learning Vector Quantization.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

The LVQ-based Counter Propagation Network - an Interpretable Information Bottleneck Approach.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020
Learning vector quantization and relevances in complex coefficient space.
Neural Comput. Appl., 2020

Variants of DropConnect in Learning vector quantization networks for evaluation of classification stability.
Neurocomputing, 2020

Quantum-Inspired Learning Vector Quantization for Classification Learning.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019
Activation Functions for Generalized Learning Vector Quantization - A Performance Comparison.
CoRR, 2019

Application of an interpretable classification model on Early Folding Residues during protein folding.
BioData Min., 2019

Investigation of Activation Functions for Generalized Learning Vector Quantization.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

Searching for the Origins of Life - Detecting RNA Life Signatures Using Learning Vector Quantization.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

Appropriate Data Density Models in Probabilistic Machine Learning Approaches for Data Analysis.
Proceedings of the Artificial Intelligence and Soft Computing, 2019

2018
Learning vector quantization classifiers for ROC-optimization.
Comput. Stat., 2018

Investigating the Influence of CPU Load, Memory Usage and Environmental Conditions on the Jittering of Android Devices.
Proceedings of the VII International Conference on Network, Communication and Computing, 2018

Probabilistic Learning Vector Quantization with Cross-Entropy for Probabilistic Class Assignments in Classification Learning.
Proceedings of the Artificial Intelligence and Soft Computing, 2018

Reliable Patient Classification in Case of Uncertain Class Labels Using a Cross-Entropy Approach.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
Can Learning Vector Quantization be an Alternative to SVM and Deep Learning? - Recent Trends and Advanced Variants of Learning Vector Quantization for Classification Learning.
J. Artif. Intell. Soft Comput. Res., 2017

Types of (dis-)similarities and adaptive mixtures thereof for improved classification learning.
Neurocomputing, 2017

Prototypes and matrix relevance learning in complex fourier space.
Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017

Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities.
Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017

2016
Integration of Auxiliary Data Knowledge in Prototype Based Vector Quantization and Classification Models
PhD thesis, 2016

Learning matrix quantization and relevance learning based on Schatten-p-norms.
Neurocomputing, 2016

Self-Adjusting Reject Options in Prototype Based Classification.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2016

Complex Variants of GLVQ Based on Wirtinger's Calculus.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2016

Low-Rank Kernel Space Representations in Prototype Learning.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2016

Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning - A Mathematical Characterization.
Proceedings of the Artificial Intelligence and Soft Computing, 2016

Adaptive dissimilarity weighting for prototype-based classification optimizing mixtures of dissimilarities.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Border-sensitive learning in generalized learning vector quantization: an alternative to support vector machines.
Soft Comput., 2015

Kernelized vector quantization in gradient-descent learning.
Neurocomputing, 2015

Mathematical Characterization of Sophisticated Variants for Relevance Learning in Learning Matrix Quantization Based on Schatten-p-norms.
Proceedings of the Artificial Intelligence and Soft Computing, 2015

Learning matrix quantization and variants of relevance learning.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Learning Vector Quantization with Adaptive Cost-Based Outlier-Rejection.
Proceedings of the Computer Analysis of Images and Patterns, 2015

2014
Lateral enhancement in adaptive metric learning for functional data.
Neurocomputing, 2014

RFSOM - Extending Self-Organizing Feature Maps with Adaptive Metrics to Combine Spatial and Textural Features for Body Pose Estimation.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Attention Based Classification Learning in GLVQ and Asymmetric Misclassification Assessment.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Optimization of General Statistical Accuracy Measures for Classification Based on Learning Vector Quantization.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Precision-Recall-Optimization in Learning Vector Quantization Classifiers for Improved Medical Classification Systems.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

2013
Regularization in Relevance Learning Vector Quantization Using l one Norms.
CoRR, 2013

Clustering by Fuzzy Neural Gas and Evaluation of Fuzzy Clusters.
Comput. Intell. Neurosci., 2013

Border-Sensitive Learning in Kernelized Learning Vector Quantization.
Proceedings of the Advances in Computational Intelligence, 2013

About analysis and robust classification of searchlight fMRI-data using machine learning classifiers.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Processing Hyperspectral Data in Machine Learning.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Regularization in relevance learning vector quantization using l1-norms.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

A sparse kernelized matrix learning vector quantization model for human activity recognition.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Border sensitive fuzzy vector quantization in semi-supervised learning.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

2012
Functional relevance learning in generalized learning vector quantization.
Neurocomputing, 2012

Gradient Based Learning in Vector Quantization Using Differentiable Kernels.
Proceedings of the Advances in Self-Organizing Maps - 9th International Workshop, 2012

Non-Euclidean Principal Component Analysis and Oja's Learning Rule - Theoretical Aspects.
Proceedings of the Advances in Self-Organizing Maps - 9th International Workshop, 2012

ICMLA Face Recognition Challenge - Results of the Team Computational Intelligence Mittweida.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Differentiable Kernels in Generalized Matrix Learning Vector Quantization.
Proceedings of the 11th International Conference on Machine Learning and Applications, 2012

Fuzzy Neural Gas for Unsupervised Vector Quantization.
Proceedings of the Artificial Intelligence and Soft Computing, 2012

Fuzzy Supervised Self-Organizing Map for Semi-supervised Vector Quantization.
Proceedings of the Artificial Intelligence and Soft Computing, 2012

Integration of Structural Expert Knowledge about Classes for Classification Using the Fuzzy Supervised Neural Gas.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Modified Conn-Index for the evaluation of fuzzy clusterings.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

2011
Sparse Functional Relevance Learning in Generalized Learning Vector Quantization.
Proceedings of the Advances in Self-Organizing Maps - 8th International Workshop, 2011

Relevance Learning in Unsupervised Vector Quantization Based on Divergences.
Proceedings of the Advances in Self-Organizing Maps - 8th International Workshop, 2011

Generalized functional relevance learning vector quantization.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011

Optimization of Parametrized Divergences in Fuzzy c-Means.
Proceedings of the 19th European Symposium on Artificial Neural Networks, 2011


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