Frank-Michael Schleif

According to our database1, Frank-Michael Schleif authored at least 137 papers between 2004 and 2020.

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

Timeline

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Bibliography

2020
Sparsification of core set models in non-metric supervised learning.
Pattern Recognit. Lett., 2020

Transfer learning extensions for the probabilistic classification vector machine.
Neurocomputing, 2020

Reactive Soft Prototype Computing for Concept Drift Streams.
Neurocomputing, 2020

Complex-valued embeddings of generic proximity data.
CoRR, 2020

Reactive Concept Drift Detection Using Coresets Over Sliding Windows.
Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, 2020

Low-Rank Subspace Override for Unsupervised Domain Adaptation.
Proceedings of the KI 2020: Advances in Artificial Intelligence, 2020

Encoding of Indefinite Proximity Data: A Structure Preserving Perspective.
Proceedings of the Pattern Recognition Applications and Methods, 2020

Structure Preserving Encoding of Non-euclidean Similarity Data.
Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods, 2020

Random Projection in the Presence of Concept Drift in Supervised Environments.
Proceedings of the Artificial Intelligence and Soft Computing, 2020

Domain Invariant Representations with Deep Spectral Alignment.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Random Projection in supervised non-stationary environments.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Analyzing Dynamic Social Media Data via Random Projection - A New Challenge for Stream Classifiers.
Proceedings of the 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems, 2020

Bridging Adversarial and Statistical Domain Transfer via Spectral Adaptation Networks.
Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020

2019
Advances in artificial neural networks, machine learning and computational intelligence: Selected papers from the 26<sup><i>th</i></sup> European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2018).
Neurocomputing, 2019

Globular cluster detection in the GAIA survey.
Neurocomputing, 2019

Domain Adaptation via Low-Rank Basis Approximation.
CoRR, 2019

Passive Concept Drift Handling via Momentum Based Robust Soft Learning Vector Quantization.
Proceedings of the Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization, 2019

Device-Free Passive Human Counting with Bluetooth Low Energy Beacons.
Proceedings of the Advances in Computational Intelligence, 2019

Reactive Soft Prototype Computing for frequent reoccurring Concept Drift.
Proceedings of the 27th European Symposium on Artificial Neural Networks, 2019

Towards a device-free passive presence detection system with Bluetooth Low Energy beacons.
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

2018
Supervised low rank indefinite kernel approximation using minimum enclosing balls.
Neurocomputing, 2018

Sparsification of Indefinite Learning Models.
Proceedings of the Structural, Syntactic, and Statistical Pattern Recognition, 2018

Sparse Transfer Classification for Text Documents.
Proceedings of the KI 2018: Advances in Artificial Intelligence, 2018

Transfer learning for the probabilistic classification vector machine.
Proceedings of the 7th Symposium on Conformal and Probabilistic Prediction and Applications, 2018

2017
Indefinite Core Vector Machine.
Pattern Recognit., 2017

Small sets of random Fourier features by kernelized Matrix LVQ.
Proceedings of the 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, 2017

Indefinite Support Vector Regression.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2017, 2017

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

Probabilistic classifiers with low rank indefinite kernels.
CoRR, 2016

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

Learning in indefinite proximity spaces - recent trends.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

Finding Small Sets of Random Fourier Features for Shift-Invariant Kernel Approximation.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

2015
Indefinite Proximity Learning: A Review.
Neural Comput., 2015

Generic probabilistic prototype based classification of vectorial and proximity data.
Neurocomputing, 2015

Metric learning for sequences in relational LVQ.
Neurocomputing, 2015

Metric and non-metric proximity transformations at linear costs.
Neurocomputing, 2015

Developments in computational intelligence and machine learning.
Neurocomputing, 2015

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

Large Scale Indefinite Kernel Fisher Discriminant.
Proceedings of the Similarity-Based Pattern Recognition - Third International Workshop, 2015

Incremental probabilistic classification vector machine with linear costs.
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

Probabilistic Classification Vector Machine at large scale.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

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

Correlation-based embedding of pairwise score data.
Neurocomputing, 2014

Learning interpretable kernelized prototype-based models.
Neurocomputing, 2014

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

Advances in artificial neural networks, machine learning, and computational intelligence (ESANN 2013).
Neurocomputing, 2014

Probabilistic Prototype Classification Using t-norms.
Proceedings of the Advances in Self-Organizing Maps and Learning Vector Quantization, 2014

High Dimensional Matrix Relevance Learning.
Proceedings of the 2014 IEEE International Conference on Data Mining Workshops, 2014

Discriminative Fast Soft Competitive Learning.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2014, 2014

Recent trends in learning of structured and non-standard data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

Proximity learning for non-standard big data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014

2013
Novel approaches in machine learning and computational intelligence.
Neurocomputing, 2013

Data Analysis of (Non-)Metric Proximities at Linear Costs.
Proceedings of the Similarity-Based Pattern Recognition - Second International Workshop, 2013

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

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

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

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

Approximation techniques for clustering dissimilarity data.
Neurocomputing, 2012

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

Large margin linear discriminative visualization by Matrix Relevance Learning.
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

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

Adaptive learning for complex-valued data.
Proceedings of the 20th European Symposium on Artificial Neural Networks, 2012

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

2011
Divergence-based classification in learning vector quantization.
Neurocomputing, 2011

Advances in artificial neural networks, machine learning, and computational intelligence.
Neurocomputing, 2011

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

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

Genetic algorithm for shift-uncertainty correction in 1-D NMR-based metabolite identifications and quantifications.
Bioinform., 2011

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

Sparse kernelized vector quantization with local dependencies.
Proceedings of the 2011 International Joint Conference on Neural Networks, 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

Recent trends in computational intelligence in life sciences.
Proceedings of the ESANN 2011, 2011

Multivariate class labeling in Robust Soft LVQ.
Proceedings of the ESANN 2011, 2011

Mathematical Foundations of the Self Organized Neighbor Embedding (SONE) for Dimension Reduction and Visualization.
Proceedings of the ESANN 2011, 2011

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

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

Advances in computational intelligence and learning (ESANN 2009).
Neurocomputing, 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

Learning vector quantization for heterogeneous structured data.
Proceedings of the ESANN 2010, 2010

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

Divergence based Learning Vector Quantization.
Proceedings of the ESANN 2010, 2010

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

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

Supervised data analysis and reliability estimation with exemplary application for spectral data.
Neurocomputing, 2009

Advances in machine learning and computational intelligence.
Neurocomputing, 2009

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

Hierarchical PCA Using Tree-SOM for the Identification of Bacteria.
Proceedings of the Advances in Self-Organizing Maps, 7th International Workshop, 2009

Funtional vector quantization by neural maps.
Proceedings of the First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2009

Matrix Metric Adaptation Linear Discriminant Analysis of Biomedical Data.
Proceedings of the Bio-Inspired Systems: Computational and Ambient Intelligence, 2009

Tanimoto Metric in Tree-SOM for Improved Representation of Mass Spectrometry Data with an Underlying Taxonomic Structure.
Proceedings of the International Conference on Machine Learning and Applications, 2009

Neural Maps and Learning Vector Quantization - Theory and Applications.
Proceedings of the ESANN 2009, 2009

Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data.
Proceedings of the Similarity-Based Clustering, 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

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

Derivatives of Pearson Correlation for Gradient-based Analysis of Biomedical Data.
Inteligencia Artif., 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

Metric adaptation for supervised attribute rating.
Proceedings of the ESANN 2008, 2008

Generalized matrix learning vector quantizer for the analysis of spectral data.
Proceedings of the ESANN 2008, 2008

Sparse Coding Neural Gas for Analysis of Nuclear Magnetic Resonance Spectroscopy.
Proceedings of the Twenty-First IEEE International Symposium on Computer-Based Medical Systems, 2008

2007
Maschinelles Lernen mit Prototypmethoden in der klinischen Proteomik.
Künstliche Intell., 2007

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

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

Association Learning in SOMs for Fuzzy-Classification.
Proceedings of the Sixth International Conference on Machine Learning and Applications, 2007

Visualization of Fuzzy Information in Fuzzy-Classification for Image Segmentation using MDS.
Proceedings of the ESANN 2007, 2007

Advances in pre-processing and model generation for mass spectrometric data analysis.
Proceedings of the Similarity-based Clustering and its Application to Medicine and Biology, 25.03., 2007

Statistical Classification and Visualization of MALDI-Imaging Data.
Proceedings of the 20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007), 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

Prototype-based fuzzy classification with local relevance for proteomics.
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

Prototype based machine learning for clinical proteomics.
Proceedings of the Ausgezeichnete Informatikdissertationen 2006, 2006

Fuzzy image segmentation with Fuzzy Labelled Neural Gas.
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

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

Prototype based machine learning for clinical proteomics.
PhD thesis, 2006

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

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


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