Barbara Hammer

According to our database1, Barbara Hammer authored at least 335 papers between 1996 and 2020.

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Bibliography

2020
Brain-inspired computing and machine learning.
Neural Comput. Appl., 2020

Time integration and reject options for probabilistic output of pairwise LVQ.
Neural Comput. Appl., 2020

Feature relevance determination for ordinal regression in the context of feature redundancies and privileged information.
Neurocomputing, 2020

Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation.
Data Sci. Eng., 2020

Intuitiveness in Active Teaching.
CoRR, 2020

Analysis of Drifting Features.
CoRR, 2020

Towards an Automatic Analysis of CHO-K1 Suspension Growth in Microfluidic Single-cell Cultivation.
CoRR, 2020

Efficient computation of contrastive explanations.
CoRR, 2020

Reservoir Memory Machines as Neural Computers.
CoRR, 2020

Counterfactual Explanations of Concept Drift.
CoRR, 2020

Supervised Learning in the Presence of Concept Drift: A modelling framework.
CoRR, 2020

Sequential Feature Classification in the Context of Redundancies.
CoRR, 2020

Randomizing the Self-Adjusting Memory for Enhanced Handling of Concept Drift.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Adversarial Attacks Hidden in Plain Sight.
Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD).
Proceedings of the 37th International Conference on Machine Learning, 2020

Balanced SAM-kNN: Online Learning with Heterogeneous Drift and Imbalanced Data.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Explaining Concept Drift by Mean of Direction.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Convex Density Constraints for Computing Plausible Counterfactual Explanations.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2020, 2020

Locally Adaptive Nearest Neighbors.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Sparse Metric Learning in Prototype-based Classification.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Efficient computation of counterfactual explanations of LVQ models.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019
Differential privacy for learning vector quantization.
Neurocomputing, 2019

A probability theoretic approach to drifting data in continuous time domains.
CoRR, 2019

On the computation of counterfactual explanations - A survey.
CoRR, 2019

DeepView: Visualizing the behavior of deep neural networks in a part of the data space.
CoRR, 2019

Non-Negative Kernel Sparse Coding for the Classification of Motion Data.
CoRR, 2019

Adversarial attacks hidden in plain sight.
CoRR, 2019

Prototype-Based Classifiers in the Presence of Concept Drift: A Modelling Framework.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Adversarial Robustness Curves.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning.
Proceedings of the International Joint Conference on Neural Networks, 2019

Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement Units.
Proceedings of the International Conference on Robotics and Automation, 2019

On the Identification of Decision Boundaries for Anomaly Detection in CPPS.
Proceedings of the IEEE International Conference on Industrial Technology, 2019

Recovering Localized Adversarial Attacks.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2019: Theoretical Neural Computation, 2019

Feature relevance bounds for ordinal regression.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Multiple-Kernel dictionary learning for reconstruction and clustering of unseen multivariate time-series.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Interpretable Multiple-Kernel Prototype Learning for Discriminative Representation and Feature Selection.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration.
Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2019

2018
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces.
Neural Process. Lett., 2018

Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM).
Knowl. Inf. Syst., 2018

Expectation maximization transfer learning and its application for bionic hand prostheses.
Neurocomputing, 2018

Incremental on-line learning: A review and comparison of state of the art algorithms.
Neurocomputing, 2018

Interpretation of linear classifiers by means of feature relevance bounds.
Neurocomputing, 2018

Statistical Mechanics of On-Line Learning Under Concept Drift.
Entropy, 2018

Progressive Data Science: Potential and Challenges.
CoRR, 2018

Automated Design of Machine Learning and Search Algorithms [Guest Editorial].
IEEE Comput. Intell. Mag., 2018

Classification of motor errors to provide real-time feedback for sports coaching in virtual reality - A case study in squats and Tai Chi pushes.
Comput. Graph., 2018

flowLearn: fast and precise identification and quality checking of cell populations in flow cytometry.
Bioinform., 2018

Interpretable machine learning with reject option.
Autom., 2018

Generation of Adversarial Examples to Prevent Misclassification of Deep Neural Network based Condition Monitoring Systems for Cyber-Physical Production Systems.
Proceedings of the 16th IEEE International Conference on Industrial Informatics, 2018

A Geometric Approach to Clustering Based Anomaly Detection for Industrial Applications.
Proceedings of the IECON 2018, 2018

Inferring Temporal Structure from Predictability in Bumblebee Learning Flight.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018

Non-negative Local Sparse Coding for Subspace Clustering.
Proceedings of the Advances in Intelligent Data Analysis XVII, 2018

Tree Edit Distance Learning via Adaptive Symbol Embeddings.
Proceedings of the 35th International Conference on Machine Learning, 2018

Enhancing Very Fast Decision Trees with Local Split-Time Predictions.
Proceedings of the IEEE International Conference on Data Mining, 2018

Confident Kernel Sparse Coding and Dictionary Learning.
Proceedings of the IEEE International Conference on Data Mining, 2018

Skill Memories for Parameterized Dynamic Action Primitives on the Pneumatically Driven Humanoid Robot Child Affetto.
Proceedings of the 2018 Joint IEEE 8th International Conference on Development and Learning and Epigenetic Robotics, 2018

Mitigating Concept Drift via Rejection.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2018, 2018

Feasibility based Large Margin Nearest Neighbor metric learning.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

Differential private relevance learning.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
Editorial: A Successful Year and Looking Forward to 2017 and Beyond.
IEEE Trans. Neural Networks Learn. Syst., 2017

Efficient kernelisation of discriminative dimensionality reduction.
Neurocomputing, 2017

The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces.
CoRR, 2017

Probabilistic extension and reject options for pairwise LVQ.
Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017

Effects of variability in synthetic training data on convolutional neural networks for 3D head reconstruction.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Linear supervised transfer learning for the large margin nearest neighbor classifier.
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence, 2017

Personalized maneuver prediction at intersections.
Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems, 2017

Label-noise-tolerant classification for streaming data.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Self-Adjusting Memory: How to Deal with Diverse Drift Types.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

An EM transfer learning algorithm with applications in bionic hand prostheses.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Feature Relevance Bounds for Linear Classification.
Proceedings of the 25th European Symposium on Artificial Neural Networks, 2017

Echo State Networks as Novel Approach for Low-Cost Myoelectric Control.
Proceedings of the Artificial Intelligence in Medicine, 2017

2016
Odor recognition in robotics applications by discriminative time-series modeling.
Pattern Anal. Appl., 2016

Adaptive structure metrics for automated feedback provision in intelligent tutoring systems.
Neurocomputing, 2016

Optimal local rejection for classifiers.
Neurocomputing, 2016

acdc - Automated Contamination Detection and Confidence estimation for single-cell genome data.
BMC Bioinform., 2016

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

Online metric learning for an adaptation to confidence drift.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

Local Reject Option for Deterministic Multi-class SVM.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Non-negative Kernel Sparse Coding for the Analysis of Motion Data.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2016, 2016

Gaussian process prediction for time series of structured data.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Choosing the best algorithm for an incremental on-line learning task.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Incremental learning algorithms and applications.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Discriminative dimensionality reduction in kernel space.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming.
Proceedings of the 9th International Conference on Educational Data Mining, 2016

Prototype-based Models for the Supervised Learning of Classification Schemes.
Proceedings of the Astroinformatics 2016, Sorrento, Italy, October 19-25, 2016, 2016

2015
Data visualization by nonlinear dimensionality reduction.
Wiley Interdiscip. Rev. Data Min. Knowl. Discov., 2015

Using Discriminative Dimensionality Reduction to Visualize Classifiers.
Neural Process. Lett., 2015

Autonomous Learning of Representations.
Künstliche Intell., 2015

Special Issue on Autonomous Learning.
Künstliche Intell., 2015

Learning Feedback in Intelligent Tutoring Systems - Report of the FIT Project, Conducted from December 2011 to March 2015.
Künstliche Intell., 2015

Median variants of learning vector quantization for learning of dissimilarity data.
Neurocomputing, 2015

Metric learning for sequences in relational LVQ.
Neurocomputing, 2015

Efficient approximations of robust soft learning vector quantization for non-vectorial data.
Neurocomputing, 2015

Parametric nonlinear dimensionality reduction using kernel t-SNE.
Neurocomputing, 2015

Efficient rejection strategies for prototype-based classification.
Neurocomputing, 2015

Optimum Reject Options for Prototype-based Classification.
CoRR, 2015

Sparse conformal prediction for dissimilarity data.
Ann. Math. Artif. Intell., 2015

Inferring Feature Relevances From Metric Learning.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2015

Discriminative dimensionality reduction for regression problems using the Fisher metric.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Automatic discovery of metagenomic structure.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Interactive online learning for obstacle classification on a mobile robot.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Combining offline and online classifiers for life-long learning.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Stationarity of Matrix Relevance LVQ.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Metric Learning in Dimensionality Reduction.
Proceedings of the ICPRAM 2015, 2015

Adaptive structure metrics for automated feedback provision in Java programming.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Certainty-based prototype insertion/deletion for classification with metric adaptation.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

Unsupervised Dimensionality Reduction for Transfer Learning.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems.
Proceedings of the 8th International Conference on Educational Data Mining, 2015

Efficient metric learning for the analysis of motion data.
Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

Visualization of Regression Models Using Discriminative Dimensionality Reduction.
Proceedings of the Computer Analysis of Images and Patterns, 2015

2014
Adaptive conformal semi-supervised vector quantization for dissimilarity data.
Pattern Recognit. Lett., 2014

Learning interpretable kernelized prototype-based models.
Neurocomputing, 2014

Special issue on new challenges in neural computation 2012.
Neurocomputing, 2014

Learning vector quantization for (dis-)similarities.
Neurocomputing, 2014

Example-based feedback provision using structured solution spaces.
Int. J. Learn. Technol., 2014

Computational Intelligence in Big Data [Guest Editorial].
IEEE Comput. Intell. Mag., 2014

Generative versus Discriminative Prototype Based Classification.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

Rejection Strategies for Learning Vector Quantization - A Comparison of Probabilistic and Deterministic Approaches.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning.
Proceedings of the Intelligent Tutoring Systems - 12th International Conference, 2014

Efficient Adaptation of Structure Metrics in Prototype-Based Classification.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Local Rejection Strategies for Learning Vector Quantization.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Relevance Learning for Dimensionality Reduction.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Supervised Generative Models for Learning Dissimilarity Data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Adaptive distance measures for sequential data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Learning and modeling big data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Rejection strategies for learning vector quantization.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Valid interpretation of feature relevance for linear data mappings.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

2013
Visualizing the quality of dimensionality reduction.
Neurocomputing, 2013

Preface: Intelligent interactive data visualization.
Data Min. Knowl. Discov., 2013

Secure Semi-supervised Vector Quantization for Dissimilarity Data.
Proceedings of the Advances in Computational Intelligence, 2013

Using Nonlinear Dimensionality Reduction to Visualize Classifiers.
Proceedings of the Advances in Computational Intelligence, 2013

Nonlinear Dimensionality Reduction for Cluster Identification in Metagenomic Samples.
Proceedings of the 17th International Conference on Information Visualisation, 2013

Sparse Prototype Representation by Core Sets.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2013, 2013

Applications of Discriminative Dimensionality Reduction.
Proceedings of the ICPRAM 2013, 2013

Discriminative Dimensionality Reduction for the Visualization of Classifiers.
Proceedings of the Pattern Recognition Applications and Methods - International Conference, 2013

A Median Variant of Generalized Learning Vector Quantization.
Proceedings of the Neural Information Processing - 20th International Conference, 2013

Towards a Domain-Independent ITS Middleware Architecture.
Proceedings of the IEEE 13th International Conference on Advanced Learning Technologies, 2013

Semi-Supervised Vector Quantization for proximity data.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Sparse approximations for kernel learning vector quantization.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Visualizing dependencies of spectral features using mutual information.
Proceedings of the 21st European Symposium on Artificial Neural Networks, 2013

Domain-Independent Proximity Measures in Intelligent Tutoring Systems.
Proceedings of the 6th International Conference on Educational Data Mining, 2013

Regularization and improved interpretation of linear data mappings and adaptive distance measures.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2013

Distance Measures for Prototype Based Classification.
Proceedings of the Brain-Inspired Computing - International Workshop, 2013

Towards Providing Feedback to Students in Absence of Formalized Domain Models.
Proceedings of the Artificial Intelligence in Education - 16th International Conference, 2013

2012
Limited Rank Matrix Learning, discriminative dimension reduction and visualization.
Neural Networks, 2012

A General Framework for Dimensionality-Reducing Data Visualization Mapping.
Neural Comput., 2012

Challenges in Neural Computation.
Künstliche Intell., 2012

Special Issue on Neural Learning Paradigms.
Künstliche Intell., 2012

Approximation techniques for clustering dissimilarity data.
Neurocomputing, 2012

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

Linear Time Relational Prototype Based Learning.
Int. J. Neural Syst., 2012

Efficient Approximations of Kernel Robust Soft LVQ.
Proceedings of the Advances in Self-Organizing Maps - 9th International Workshop, 2012

How to Visualize Large Data Sets?
Proceedings of the Advances in Self-Organizing Maps - 9th International Workshop, 2012

Cluster Based Feedback Provision Strategies in Intelligent Tutoring Systems.
Proceedings of the Intelligent Tutoring Systems - 11th International Conference, 2012

Patch Processing for Relational Learning Vector Quantization.
Proceedings of the Advances in Neural Networks - ISNN 2012, 2012

Relevance learning for short high-dimensional time series in the life sciences.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Linear basis-function t-SNE for fast nonlinear dimensionality reduction.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

A Conformal Classifier for Dissimilarity Data.
Proceedings of the Artificial Intelligence Applications and Innovations, 2012

Discriminative Dimensionality Reduction Mappings.
Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

Fast approximated relational and kernel clustering.
Proceedings of the 21st International Conference on Pattern Recognition, 2012

Learning Relevant Time Points for Time-Series Data in the Life Sciences.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

White Box Classification of Dissimilarity Data.
Proceedings of the Hybrid Artificial Intelligent Systems - 7th International Conference, 2012

Visualizing the quality of dimensionality reduction.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Relevance learning for time series inspection.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Out-of-sample kernel extensions for nonparametric dimensionality reduction.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Recent developments in clustering algorithms.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces.
Proceedings of the DeLFI 2012, 2012

How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning?
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2012

Kernel Robust Soft Learning Vector Quantization.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2012

Soft Competitive Learning for Large Data Sets.
Proceedings of the New Trends in Databases and Information Systems, 2012

2011
Relational generative topographic mapping.
Neurocomputing, 2011

Relevance learning in generative topographic mapping.
Neurocomputing, 2011

Neighbor embedding XOM for dimension reduction and visualization.
Neurocomputing, 2011

Local matrix adaptation in topographic neural maps.
Neurocomputing, 2011

Efficient Kernelized Prototype Based Classification.
Int. J. Neural Syst., 2011

Learning in the context of very high dimensional data (Dagstuhl Seminar 11341).
Dagstuhl Reports, 2011

How to Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix
CoRR, 2011

Supervised learning of short and high-dimensional temporal sequences for life science measurements
CoRR, 2011

Topographic Mapping of Dissimilarity Data.
Proceedings of the Advances in Self-Organizing Maps - 8th International Workshop, 2011

A General Framework for Dimensionality Reduction for Large Data Sets.
Proceedings of the Advances in Self-Organizing Maps - 8th International Workshop, 2011

Linear Time Heuristics for Topographic Mapping of Dissimilarity Data.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2011, 2011

Prototype-Based Classification of Dissimilarity Data.
Proceedings of the Advances in Intelligent Data Analysis X - 10th International Symposium, 2011

Relational Extensions of Learning Vector Quantization.
Proceedings of the Neural Information Processing - 18th International Conference, 2011

Accelerating Kernel Neural Gas.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2011, 2011

Patch Affinity Propagation.
Proceedings of the ESANN 2011, 2011

Generalized functional relevance learning vector quantization.
Proceedings of the ESANN 2011, 2011

Supervised dimension reduction mappings.
Proceedings of the ESANN 2011, 2011

Dimensionality reduction mappings.
Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2011

Accelerating kernel clustering for biomedical data analysis.
Proceedings of the 2011 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 2011

2010
Regularization in matrix relevance learning.
IEEE Trans. Neural Networks, 2010

Local matrix learning in clustering and applications for manifold visualization.
Neural Networks, 2010

Window-Based Example Selection in Learning Vector Quantization.
Neural Comput., 2010

Topographic Mapping of Large Dissimilarity Data Sets.
Neural Comput., 2010

Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints.
Knowl. Inf. Syst., 2010

Hyperparameter learning in probabilistic prototype-based models.
Neurocomputing, 2010

Median fuzzy c-means for clustering dissimilarity data.
Neurocomputing, 2010

Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data.
Neurocomputing, 2010

Perspectives and challenges for recurrent neural network training.
Log. J. IGPL, 2010

Visualizing Dissimilarity Data Using Generative Topographic Mapping.
Proceedings of the KI 2010: Advances in Artificial Intelligence, 2010

Generalized Derivative Based Kernelized Learning Vector Quantization.
Proceedings of the Intelligent Data Engineering and Automated Learning, 2010

Divergence Based Online Learning in Vector Quantization.
Proceedings of the Artificial Intelligence and Soft Computing, 2010

Sparse representation of data.
Proceedings of the ESANN 2010, 2010

Relational Generative Topographic Map.
Proceedings of the ESANN 2010, 2010

Relevance learning in generative topographic maps.
Proceedings of the ESANN 2010, 2010

Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization.
Proceedings of the ESANN 2010, 2010

10302 Summary - Learning paradigms in dynamic environments.
Proceedings of the Learning paradigms in dynamic environments, 25.07. - 30.07.2010, 2010

10302 Abstracts Collection - Learning paradigms in dynamic environments.
Proceedings of the Learning paradigms in dynamic environments, 25.07. - 30.07.2010, 2010

Some steps towards a general principle for dimensionality reduction mappings.
Proceedings of the Learning paradigms in dynamic environments, 25.07. - 30.07.2010, 2010

The Mathematics of Divergence Based Online Learning in Vector Quantization.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2010

Clustering Very Large Dissimilarity Data Sets.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2010

Global Coordination Based on Matrix Neural Gas for Dynamic Texture Synthesis.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2010

2009
Metric Learning for Prototype-Based Classification.
Proceedings of the Innovations in Neural Information Paradigms and Applications, 2009

Prototype Based Classification in Bioinformatics.
Proceedings of the Encyclopedia of Artificial Intelligence (3 Volumes), 2009

Adaptive Relevance Matrices in Learning Vector Quantization.
Neural Comput., 2009

Distance Learning in Discriminative Vector Quantization.
Neural Comput., 2009

Patch clustering for massive data sets.
Neurocomputing, 2009

Cancer informatics by prototype networks in mass spectrometry.
Artif. Intell. Medicine, 2009

Functional Principal Component Learning Using Oja's Method and Sobolev Norms.
Proceedings of the Advances in Self-Organizing Maps, 7th International Workshop, 2009

Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means.
Proceedings of the Advances in Self-Organizing Maps, 7th International Workshop, 2009

Graph-Based Representation of Symbolic Musical Data.
Proceedings of the Graph-Based Representations in Pattern Recognition, 2009

Equilibrium properties of off-line LVQ.
Proceedings of the ESANN 2009, 2009

Hyperparameter Learning in Robust Soft LVQ.
Proceedings of the ESANN 2009, 2009

Recent advances in efficient learning of recurrent networks.
Proceedings of the ESANN 2009, 2009

Median Variant of Fuzzy c-Means.
Proceedings of the ESANN 2009, 2009

Nonlinear Discriminative Data Visualization.
Proceedings of the ESANN 2009, 2009

Some Theoretical Aspects of the Neural Gas Vector Quantizer.
Proceedings of the Similarity-Based Clustering, 2009

Median Topographic Maps for Biomedical Data Sets.
Proceedings of the Similarity-Based Clustering, 2009

09081 Summary - Similarity-based learning on structures.
Proceedings of the Similarity-based learning on structures, 15.02. - 20.02.2009, 2009

09081 Abstracts Collection - Similarity-based learning on structures.
Proceedings of the Similarity-based learning on structures, 15.02. - 20.02.2009, 2009

Nonlinear Dimension Reduction and Visualization of Labeled Data.
Proceedings of the Computer Analysis of Images and Patterns, 13th International Conference, 2009

2008
Analysis of Spectral Data in Clinical Proteomics by Use of Learning Vector Quantizers.
Proceedings of the Computational Intelligence in Biomedicine and Bioinformatics, 2008

Learning dynamics and robustness of vector quantization and neural gas.
Neurocomputing, 2008

Fuzzy classification using information theoretic learning vector quantization.
Neurocomputing, 2008

Prototype based fuzzy classification in clinical proteomics.
Int. J. Approx. Reason., 2008

Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods.
Briefings Bioinform., 2008

Thinning Mesh Animations.
Proceedings of the 13th International Fall Workshop on Vision, Modeling, and Visualization, 2008

Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity.
Proceedings of the Advances in Neuro-Information Processing, 15th International Conference, 2008

Matrix Learning for Topographic Neural Maps.
Proceedings of the Artificial Neural Networks, 2008

Magnification Control in Relational Neural Gas.
Proceedings of the ESANN 2008, 2008

Parallelizing single patch pass clustering.
Proceedings of the ESANN 2008, 2008

08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications.
Proceedings of the Recurrent Neural Networks - Models, Capacities, and Applications, 20.01., 2008

08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications.
Proceedings of the Recurrent Neural Networks - Models, Capacities, and Applications, 20.01., 2008

Robust Centroid-Based Clustering using Derivatives of Pearson Correlation.
Proceedings of the First International Conference on Biomedical Electronics and Devices, 2008

Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics.
Proceedings of the Artificial Neural Networks in Pattern Recognition, Third IAPR Workshop, 2008

Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets.
Proceedings of the Artificial Neural Networks in Pattern Recognition, Third IAPR Workshop, 2008

Single Pass Clustering and Classification of Large Dissimilarity Datasets.
Proceedings of the International Conference on Artificial Intelligence and Pattern Recognition, 2008

2007
Markovian Bias of Neural-based Architectures With Feedback Connections.
Proceedings of the Perspectives of Neural-Symbolic Integration, 2007

Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties.
Proceedings of the Perspectives of Neural-Symbolic Integration, 2007

Dynamics and Generalization Ability of LVQ Algorithms.
J. Mach. Learn. Res., 2007

Margin-based active learning for LVQ networks.
Neurocomputing, 2007

Magnification control for batch neural gas.
Neurocomputing, 2007

Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps.
Proceedings of the Applications of Fuzzy Sets Theory, 2007

Relational Neural Gas.
Proceedings of the KI 2007: Advances in Artificial Intelligence, 2007

Fuzzy Labeled Self-Organizing Map for Classification of Spectra.
Proceedings of the Computational and Ambient Intelligence, 2007

Supervised Neural Gas for Classification of Functional Data and Its Application to the Analysis of Clinical Proteom Spectra.
Proceedings of the Computational and Ambient Intelligence, 2007

Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes.
Proceedings of the Computational and Ambient Intelligence, 2007

Intuitive Clustering of Biological Data.
Proceedings of the International Joint Conference on Neural Networks, 2007

Relational Topographic Maps.
Proceedings of the Advances in Intelligent Data Analysis VII, 2007

On the dynamics of Vector Quantization and Neural Gas.
Proceedings of the ESANN 2007, 2007

Relevance matrices in LVQ.
Proceedings of the ESANN 2007, 2007

How to process uncertainty in machine learning?.
Proceedings of the ESANN 2007, 2007

Learning Vector Quantization: generalization ability and dynamics of competing prototypes.
Proceedings of the Similarity-based Clustering and its Application to Medicine and Biology, 25.03., 2007

A general framework for unsupervised preocessing of structured data.
Proceedings of the Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04., 2007

Relational Clustering.
Proceedings of the Similarity-based Clustering and its Application to Medicine and Biology, 25.03., 2007

07131 Abstracts Collection -- Similarity-based Clustering and its Application to Medicine and Biology.
Proceedings of the Similarity-based Clustering and its Application to Medicine and Biology, 25.03., 2007

07131 Summary -- Similarity-based Clustering and its Application to Medicine and Biology.
Proceedings of the Similarity-based Clustering and its Application to Medicine and Biology, 25.03., 2007

2006
Comparison of relevance learning vector quantization with other metric adaptive classification methods.
Neural Networks, 2006

Fuzzy classification by fuzzy labeled neural gas.
Neural Networks, 2006

Performance analysis of LVQ algorithms: A statistical physics approach.
Neural Networks, 2006

Batch and median neural gas.
Neural Networks, 2006

Effizient Klassifizieren und Clustern: Lernparadigmen von Vektorquantisierern.
Künstliche Intell., 2006

Prototype-based fuzzy classification with local relevance for proteomics.
Neurocomputing, 2006

Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis.
Neurocomputing, 2006

Learning vector quantization: The dynamics of winner-takes-all algorithms.
Neurocomputing, 2006

Prototype Based Classification Using Information Theoretic Learning.
Proceedings of the Neural Information Processing, 13th International Conference, 2006

Learning Vector Quantization Classification with Local Relevance Determination for Medical Data.
Proceedings of the Artificial Intelligence and Soft Computing, 2006

Neural networks and machine learning in bioinformatics - theory and applications.
Proceedings of the ESANN 2006, 2006

Analysis and Visualization of Proteomic Data by Fuzzy Labeled Self-Organizing Maps.
Proceedings of the 19th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2006), 2006

Perspectives of Self-adapted Self-organizing Clustering in Organic Computing.
Proceedings of the Biologically Inspired Approaches to Advanced Information Technology, 2006

Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes.
Proceedings of the Artificial Neural Networks in Pattern Recognition, Second IAPR Workshop, 2006

Supervised Batch Neural Gas.
Proceedings of the Artificial Neural Networks in Pattern Recognition, Second IAPR Workshop, 2006

2005
On approximate learning by multi-layered feedforward circuits.
Theor. Comput. Sci., 2005

On the Generalization Ability of GRLVQ Networks.
Neural Process. Lett., 2005

Supervised Neural Gas with General Similarity Measure.
Neural Process. Lett., 2005

Special issue on neural networks and kernel methods for structured domains.
Neural Networks, 2005

Universal Approximation Capability of Cascade Correlation for Structures.
Neural Comput., 2005

Unsupervised recursive sequence processing.
Neurocomputing, 2005

Merge SOM for temporal data.
Neurocomputing, 2005

Improving iterative repair strategies for scheduling with the SVM.
Neurocomputing, 2005

New Aspects in Neurocomputing.
Neurocomputing, 2005

Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data.
Proceedings of the Fuzzy Logic and Applications, 6th International Workshop, 2005

Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning.
Proceedings of the Fourth International Conference on Machine Learning and Applications, 2005

Relevance determination in reinforcement learning.
Proceedings of the ESANN 2005, 2005

Classification using non-standard metrics.
Proceedings of the ESANN 2005, 2005

Relevance learning for mental disease classification.
Proceedings of the ESANN 2005, 2005

The dynamics of Learning Vector Quantization.
Proceedings of the ESANN 2005, 2005

2004
Recursive self-organizing network models.
Neural Networks, 2004

A general framework for unsupervised processing of structured data.
Neurocomputing, 2004

Supervised relevance neural gas and unified maximum separability analysis for classification of mass spectrometric data.
Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004

Relevance LVQ versus SVM.
Proceedings of the Artificial Intelligence and Soft Computing, 2004

Self-organizing context learning.
Proceedings of the ESANN 2004, 2004

Neural methods for non-standard data.
Proceedings of the ESANN 2004, 2004

On Early Stages of Learning in Connectionist Models with Feedback Connections.
Proceedings of the Compositional Connectionism in Cognitive Science, 2004

2003
A Note on the Universal Approximation Capability of Support Vector Machines.
Neural Process. Lett., 2003

Neural maps in remote sensing image analysis.
Neural Networks, 2003

Architectural Bias in Recurrent Neural Networks: Fractal Analysis.
Neural Comput., 2003

Recurrent Neural Networks with Small Weights Implement Definite Memory Machines.
Neural Comput., 2003

Unsupervised Recursive Sequence Processing.
Proceedings of the ESANN 2003, 2003

Mathematical Aspects of Neural Networks.
Proceedings of the ESANN 2003, 2003

2002
Generalized relevance learning vector quantization.
Neural Networks, 2002

Recurrent networks for structured data - A unifying approach and its properties.
Cogn. Syst. Res., 2002

Learning Vector Quantization for Multimodal Data.
Proceedings of the Artificial Neural Networks, 2002

Rule Extraction from Self-Organizing Networks.
Proceedings of the Artificial Neural Networks, 2002

Batch-RLVQ.
Proceedings of the ESANN 2002, 2002

Perspectives on learning with recurrent neural networks.
Proceedings of the ESANN 2002, 2002

A general framework for unsupervised processing of structured data.
Proceedings of the ESANN 2002, 2002

2001
Generalization Ability of Folding Networks.
IEEE Trans. Knowl. Data Eng., 2001

Estimating Relevant Input Dimensions for Self-organizing Algorithms.
Proceedings of the Advances in Self-Organising Maps, 2001

Generalized Relevance LVQ for Time Series.
Proceedings of the Artificial Neural Networks, 2001

On the Generalization Ability of Recurrent Networks.
Proceedings of the Artificial Neural Networks, 2001

Input pruning for neural gas architectures.
Proceedings of the ESANN 2001, 2001

Relevance determination in Learning Vector Quantization.
Proceedings of the ESANN 2001, 2001

2000
On the approximation capability of recurrent neural networks.
Neurocomputing, 2000

Limitations of hybrid systems.
Proceedings of the ESANN 2000, 2000

1999
Learning with recurrent neural networks.
PhD thesis, 1999

On the Learnability of Recursive Data.
Math. Control. Signals Syst., 1999

Approximation capabilities of folding networks.
Proceedings of the ESANN 1999, 1999

1998
Training a sigmoidal network is difficult.
Proceedings of the ESANN 1998, 1998

1997
Generalization of Elman Networks.
Proceedings of the Artificial Neural Networks, 1997

1996
Theoretische Informatik - eine problemorientierte Einführung.
Springer-Lehrbuch, Springer, ISBN: 978-3-540-60860-8, 1996


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