Barbara Hammer | Academic Influence

Barbara Hammer's AcademicInfluence.com Rankings

Barbara Hammer

Computer Science

#6209

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#6548

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Database

#3317

World Rank

#3457

Historical Rank

computer-science Degrees

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Computer Science

Barbara Hammer's Degrees

PhD Computer Science University of Stuttgart
Masters Computer Science University of Stuttgart
Bachelors Computer Science University of Stuttgart

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Barbara Hammer's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Generalized relevance learning vector quantization (2002) (468)
Adaptive Relevance Matrices in Learning Vector Quantization (2009) (364)
Neural Smithing – Supervised Learning in Feedforward Artificial Neural Networks (2001) (296)
Incremental learning algorithms and applications (2016) (236)
Incremental on-line learning: A review and comparison of state of the art algorithms (2018) (232)
Neural maps in remote sensing image analysis (2003) (184)
Supervised Neural Gas with General Similarity Measure (2005) (173)
Parametric nonlinear dimensionality reduction using kernel t-SNE (2015) (168)
Batch and median neural gas (2006) (163)
KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift (2016) (154)
Merge SOM for temporal data (2005) (132)
Recursive self-organizing network models (2004) (131)
Distance Learning in Discriminative Vector Quantization (2009) (118)
A Note on the Universal Approximation Capability of Support Vector Machines (2003) (116)
A general framework for unsupervised processing of structured data (2004) (115)
Limited Rank Matrix Learning, discriminative dimension reduction and visualization (2012) (113)
On the approximation capability of recurrent neural networks (2000) (113)
Topographic Mapping of Large Dissimilarity Data Sets (2010) (110)
Dynamics and Generalization Ability of LVQ Algorithms (2007) (110)
Prototype-based models in machine learning. (2016) (106)
On the Generalization Ability of GRLVQ Networks (2005) (98)
A General Framework for Dimensionality-Reducing Data Visualization Mapping (2012) (97)
Relevance determination in Learning Vector Quantization (2001) (91)
Regularization in Matrix Relevance Learning (2010) (91)
Perspectives of Neural-Symbolic Integration (2007) (91)
Learning vector quantization for (dis-)similarities (2014) (74)
Visualizing the quality of dimensionality reduction (2013) (70)
Data visualization by nonlinear dimensionality reduction (2015) (65)
Learning with recurrent neural networks (2000) (65)
Recurrent Neural Networks with Small Weights Implement Definite Memory Machines (2003) (62)
Adaptive local dissimilarity measures for discriminative dimension reduction of labeled data (2010) (61)
Classification of mass-spectrometric data in clinical proteomics using learning vector quantization methods (2007) (59)
Exploratory Observation Machine (XOM) with Kullback-Leibler Divergence for Dimensionality Reduction and Visualization (2010) (58)
Neighbor embedding XOM for dimension reduction and visualization (2011) (56)
Universal Approximation Capability of Cascade Correlation for Structures (2005) (51)
Learning vector quantization: The dynamics of winner-takes-all algorithms (2006) (51)
Fuzzy classification by fuzzy labeled neural gas (2006) (50)
Neural Gas for Sequences (2003) (49)
Median fuzzy c-means for clustering dissimilarity data (2010) (46)
Performance analysis of LVQ algorithms: A statistical physics approach (2006) (43)
Functional relevance learning in generalized learning vector quantization (2012) (43)
Relevance matrices in LVQ (2007) (42)
Efficient Kernelized Prototype Based Classification (2011) (42)
Mathematical Aspects of Neural Networks (2003) (42)
Relevance LVQ versus SVM (2004) (42)
Relational Neural Gas (2007) (41)
Compositionality in Neural Systems (2002) (41)
The Continuous Hint Factory - Providing Hints in Vast and Sparsely Populated Edit Distance Spaces (2017) (41)
Unsupervised Recursive Sequence Processing (2003) (41)
Neural methods for non-standard data (2004) (40)
Generalized relevance LVQ (GRLVQ) with correlation measures for gene expression analysis (2006) (38)
Interactive online learning for obstacle classification on a mobile robot (2015) (38)
Markovian Bias of Neural-based Architectures With Feedback Connections (2007) (37)
Efficient rejection strategies for prototype-based classification (2015) (37)
Magnification control for batch neural gas (2007) (37)
On the computation of counterfactual explanations - A survey (2019) (35)
Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM) (2017) (35)
Architectural Bias in Recurrent Neural Networks: Fractal Analysis (2002) (34)
Out-of-sample kernel extensions for nonparametric dimensionality reduction (2012) (34)
Distance Measures for Prototype Based Classification (2013) (34)
Comparison of relevance learning vector quantization with other metric adaptive classification methods (2006) (33)
Margin based Active Learning for LVQ Networks (2007) (33)
Self-Organizing Maps for Time Series (2005) (33)
Local matrix adaptation in topographic neural maps (2011) (32)
Recurrent networks for structured data – A unifying approach and its properties (2002) (32)
Linear basis-function t-SNE for fast nonlinear dimensionality reduction (2012) (31)
Optimal local rejection for classifiers (2016) (31)
Similarity-Based Clustering, Recent Developments and Biomedical Applications [outcome of a Dagstuhl Seminar] (2009) (31)
Metric learning for sequences in relational LVQ (2015) (31)
Recent advances in efficient learning of recurrent networks (2009) (31)
Example-based feedback provision using structured solution spaces (2014) (31)
Progressive Data Science: Potential and Challenges (2018) (31)
Domain-Independent Proximity Measures in Intelligent Tutoring Systems (2013) (30)
flowLearn: fast and precise identification and quality checking of cell populations in flow cytometry (2018) (30)
Patch clustering for massive data sets (2009) (30)
Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis After Electrode Shift (2017) (30)
Topographic Processing of Relational Data (2007) (29)
Generalization Ability of Folding Networks (2001) (29)
Rule Extraction from Self-Organizing Networks (2002) (29)
Interpretable machine learning with reject option (2018) (29)
Linear Time Relational Prototype Based Learning (2012) (29)
Convex Density Constraints for Computing Plausible Counterfactual Explanations (2020) (28)
Nonlinear Dimensionality Reduction for Cluster Identification in Metagenomic Samples (2013) (28)
Hyperparameter learning in probabilistic prototype-based models (2010) (27)
Metric Learning for Prototype-Based Classification (2009) (26)
Neural networks can approximate mappings on structured objects (1997) (26)
Using Discriminative Dimensionality Reduction to Visualize Classifiers (2015) (25)
Relational Topographic Maps (2007) (25)
Relational Generative Topographic Map (2011) (25)
Adaptive structure metrics for automated feedback provision in intelligent tutoring systems (2016) (25)
Cancer informatics by prototype networks in mass spectrometry (2009) (25)
Classification using non-standard metrics (2005) (24)
Prototype based fuzzy classification in clinical proteomics (2008) (24)
How to Evaluate Dimensionality Reduction? - Improving the Co-ranking Matrix (2011) (24)
Odor recognition in robotics applications by discriminative time-series modeling (2016) (24)
Neural networks and machine learning in bioinformatics - theory and applications (2006) (23)
Discriminative visualization by limited rank matrix learning (2008) (23)
Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning (2019) (23)
Supervised Neural Gas for Learning Vector Quantization (2002) (23)
Supervised Batch Neural Gas (2006) (23)
Learning interpretable kernelized prototype-based models (2014) (23)
Machine Learning in Non-Stationary Environments (2021) (23)
Graph-Based Representation of Symbolic Musical Data (2009) (23)
Improving iterative repair strategies for scheduling with the SVM (2003) (22)
Stationarity of Matrix Relevance LVQ (2015) (22)
Prototype based recognition of splice sites (2005) (22)
Median variants of learning vector quantization for learning of dissimilarity data (2015) (22)
How to process uncertainty in machine learning? (2007) (22)
Self-Adjusting Reject Options in Prototype Based Classification (2016) (21)
Artificial Neural Networks and Machine Learning – ICANN 2018 (2018) (21)
Computational Intelligence in Big Data [Guest Editorial] (2014) (21)
Classification of motor errors to provide real-time feedback for sports coaching in virtual reality - A case study in squats and Tai Chi pushes (2018) (21)
acdc – Automated Contamination Detection and Confidence estimation for single-cell genome data (2016) (20)
The Nystrom approximation for relational generative topographic mappings (2010) (20)
Computational Intelligence in Big Data (2014) (20)
Evaluating Robustness of Counterfactual Explanations (2021) (19)
Approximation techniques for clustering dissimilarity data (2012) (19)
Relevance learning in generative topographic mapping (2011) (19)
Data Mining and Machine Learning I (2007) (19)
Expectation maximization transfer learning and its application for bionic hand prostheses (2017) (19)
Choosing the best algorithm for an incremental on-line learning task (2016) (19)
Feedback Provision Strategies in Intelligent Tutoring Systems Based on Clustered Solution Spaces (2012) (19)
Generalized Relevance LVQ for Time Series (2001) (19)
Learning Vector Quantization for Multimodal Data (2002) (18)
Learning dynamics and robustness of vector quantization and neural gas (2008) (18)
Self-Adjusting Memory: How to Deal with Diverse Drift Types (2017) (18)
Generative versus Discriminative Prototype Based Classification (2014) (18)
Regularization and improved interpretation of linear data mappings and adaptive distance measures (2013) (18)
Window-Based Example Selection in Learning Vector Quantization (2010) (18)
Efficient approximations of robust soft learning vector quantization for non-vectorial data (2015) (18)
Approximation capabilities of folding networks (1999) (17)
Special issue on neural networks and kernel methods for structured domains (2005) (17)
Fuzzy Labeled Self-Organizing Map with Label-Adjusted Prototypes (2006) (17)
Supervised Neural Gas and Relevance Learning in Learning Vector Quantization (2003) (17)
How to Select an Example? A Comparison of Selection Strategies in Example-Based Learning (2014) (17)
Perspectives on learning with recurrent neural networks (2002) (17)
On approximate learning by multi-layered feedforward circuits (2000) (16)
Mitigating Concept Drift via Rejection (2018) (16)
Accelerating Relational Clustering Algorithms With Sparse Prototype Representation (2007) (16)
Fuzzy Variant of Affinity Propagation in Comparison to Median Fuzzy c-Means (2009) (16)
On the Learnability of Recursive Data (1999) (16)
On the Generalization Ability of Prototype-Based Classifiers with Local Relevance Determination (2005) (16)
Learning Feedback in Intelligent Tutoring Systems (2015) (16)
Rejection Strategies for Learning Vector Quantization - A Comparison of Probabilistic and Deterministic Approaches (2014) (15)
Tutorial: Perspectives on Learning with RNNs (2002) (15)
Monitoring technical systems with prototype based clustering (2003) (15)
Batch neural gas (15)
Cluster Based Feedback Provision Strategies in Intelligent Tutoring Systems (2012) (15)
Prototype-based fuzzy classification with local relevance for proteomics (2006) (15)
Dynamical analysis of LVQ type learning rules (2005) (15)
Fuzzy Labeled Soft Nearest Neighbor Classification with Relevance Learning (2005) (15)
Generalized Derivative Based Kernelized Learning Vector Quantization (2010) (15)
Statistical Mechanics of On-Line Learning Under Concept Drift (2018) (15)
Prototype-Based Classification of Dissimilarity Data (2011) (15)
Self-organizing context learning (2004) (15)
Adversarial attacks hidden in plain sight (2019) (14)
Adaptive conformal semi-supervised vector quantization for dissimilarity data (2014) (14)
Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming (2016) (14)
Explanation as a Social Practice: Toward a Conceptual Framework for the Social Design of AI Systems (2021) (14)
Generalization of Elman Networks (1997) (14)
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces (2017) (14)
Estimating Relevant Input Dimensions for Self-organizing Algorithms (2001) (14)
Stationarity of Matrix Relevance Learning Vector Quantization (2009) (13)
Interpretation of linear classifiers by means of feature relevance bounds (2018) (13)
Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation (2019) (13)
Efficient computation of counterfactual explanations of LVQ models (2019) (13)
Local Metric Adaptation for Soft Nearest Prototype Classification to Classify Proteomic Data (2005) (13)
Occupy the Dream (2013) (13)
The Mathematics of Divergence Based Online Learning in Vector Quantization (2010) (13)
Local matrix learning in clustering and applications for manifold visualization (2010) (13)
Matrix Learning in Learning Vector Quantization (2006) (13)
Analysis and Visualization of Proteomic Data by Fuzzy Labeled Self-Organizing Maps (2006) (13)
Learning Vector Quantization: generalization ability and dynamics of competing prototypes (2007) (12)
Fuzzy Labeled Neural GAS for Fuzzy Classification (2005) (12)
Differential privacy for learning vector quantization (2019) (12)
Fuzzy classification using information theoretic learning vector quantization (2008) (12)
Relational Extensions of Learning Vector Quantization (2011) (12)
Topographic Mapping of Dissimilarity Data (2011) (12)
Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties (2007) (12)
Recent developments in clustering algorithms (2012) (12)
Rejection strategies for learning vector quantization (2014) (12)
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction (2019) (12)
Decentralized control and local information for robust and adaptive decentralized Deep Reinforcement Learning (2021) (11)
Supervised relevance neural gas and unified maximum separability analysis for classification of mass spectrometric data (2004) (11)
Combining offline and online classifiers for life-long learning (2015) (11)
Generalized functional relevance learning vector quantization (2011) (11)
Learning in the context of very high dimensional data (Dagstuhl Seminar 11341) (2011) (11)
Discriminative Dimensionality Reduction Mappings (2012) (11)
Functional Principal Component Learning Using Oja's Method and Sobolev Norms (2009) (11)
Kernel Robust Soft Learning Vector Quantization (2012) (11)
A Median Variant of Generalized Learning Vector Quantization (2013) (11)
Divergence Based Online Learning in Vector Quantization (2010) (11)
Dimensionality reduction mappings (2011) (11)
Advanced metric adaptation in Generalized LVQ for classification of mass spectrometry data (2007) (11)
Towards Non-Parametric Drift Detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD) (2020) (10)
Adaptive structure metrics for automated feedback provision in Java programming (2015) (10)
Matrix Learning for Topographic Neural Maps (2008) (10)
Perspectives on learning symbolic data with connectionistic systems (2003) (10)
Neural gas for surface reconstruction (2007) (10)
Training a sigmoidal network is difficult (1998) (10)
White Box Classification of Dissimilarity Data (2012) (10)
Personalized maneuver prediction at intersections (2017) (10)
Hyperparameter Learning in Robust Soft LVQ (2009) (10)
Learning Relevant Time Points for Time-Series Data in the Life Sciences (2012) (9)
Automated Design of Machine Learning and Search Algorithms [Guest Editorial] (2018) (9)
Nonlinear Discriminative Data Visualization (2009) (9)
Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting (2022) (9)
Non-negative Kernel Sparse Coding for the Analysis of Motion Data (2016) (9)
Adaptive distance measures for sequential data (2014) (9)
Valid interpretation of feature relevance for linear data mappings (2014) (9)
Linear Supervised Transfer Learning for Generalized Matrix LVQ (2016) (9)
Some Complexity Results for Perceptron Networks (1998) (9)
Learning and modeling big data (2014) (9)
Generation of Adversarial Examples to Prevent Misclassification of Deep Neural Network based Condition Monitoring Systems for Cyber-Physical Production Systems (2018) (9)
Patch Relational Neural Gas - Clustering of Huge Dissimilarity Datasets (2008) (8)
Neural Gas Clustering for Dissimilarity Data with Continuous Prototypes (2007) (8)
A Geometric Approach to Clustering Based Anomaly Detection for Industrial Applications (2018) (8)
Discriminatory Data Mapping by Matrix-Based Supervised Learning Metrics (2008) (8)
Neural networks with small weights implement finite memory machines (2002) (8)
Special Issue on Autonomous Learning (2015) (8)
Universal approximation of mappings on structured objects using the folding architecture (1996) (8)
Recent trends in streaming data analysis, concept drift and analysis of dynamic data sets (2019) (8)
Fast approximated relational and kernel clustering (2012) (8)
A Toolbox for Adaptive Sequence Dissimilarity Measures for Intelligent Tutoring Systems (2015) (8)
Evolving trees for the retrieval of mass spectrometry-based bacteria fingerprints (2010) (8)
Graph Edit Networks (2021) (8)
Supervised Neural Gas for Classification of Functional Data and Its Application to the Analysis of Clinical Proteom Spectra (2007) (8)
Comparison of Cluster Algorithms for the Analysis of Text Data Using Kolmogorov Complexity (2009) (8)
Interpretable Discriminative Dimensionality Reduction and Feature Selection on the Manifold (2019) (7)
Parallelizing single patch pass clustering (2008) (7)
Some Theoretical Aspects of the Neural Gas Vector Quantizer (2009) (7)
Local Rejection Strategies for Learning Vector Quantization (2014) (7)
Single pass clustering for large data sets (2007) (7)
Towards a Domain-Independent ITS Middleware Architecture (2013) (7)
The Artist as Teacher: Problems and Experiments (1984) (7)
The dynamics of Learning Vector Quantization (2005) (7)
Efficient kernelisation of discriminative dimensionality reduction (2017) (6)
Convex optimization for actionable \& plausible counterfactual explanations (2021) (6)
Semi-Supervised Vector Quantization for proximity data (2013) (6)
Unsupervised Transfer Learning for Time Series via Self-Predictive Modelling - First Results (2017) (6)
How to visualize a classifier (2012) (6)
A Conformal Classifier for Dissimilarity Data (2012) (6)
Uncommon History: An Interview with Barbara Hammer (1994) (6)
Median Topographic Maps for Biomedical Data Sets (2009) (6)
How to Visualize Large Data Sets? (2012) (6)
On the effect of clustering on quality assessment measures for dimensionality reduction (2010) (6)
Inferring Feature Relevances From Metric Learning (2015) (6)
Sparse conformal prediction for dissimilarity data (2015) (6)
Challenges in Neural Computation (2012) (6)
Supervised Generative Models for Learning Dissimilarity Data (2014) (6)
A General Framework for Dimensionality Reduction for Large Data Sets (2011) (6)
Towards Providing Feedback to Students in Absence of Formalized Domain Models (2013) (6)
Supervised median neural gas (2006) (6)
Efficient Approximations of Kernel Robust Soft LVQ (2012) (5)
Prototype-based classifiers in the presence of concept drift: A modelling framework (2019) (5)
Skill Memories for Parameterized Dynamic Action Primitives on the Pneumatically Driven Humanoid Robot Child Affetto (2018) (5)
Feature relevance bounds for ordinal regression (2019) (5)
Gaussian process prediction for time series of structured data (2016) (5)
Feature Relevance Bounds for Linear Classification (2017) (5)
Balanced SAM-kNN: Online Learning with Heterogeneous Drift and Imbalanced Data (2020) (5)
Counterfactual Explanations of Concept Drift (2020) (5)
Enhancing Very Fast Decision Trees with Local Split-Time Predictions (2018) (5)
Supervised median clustering (2006) (5)
Estimating the electrical power output of industrial devices with end-to-end time-series classification in the presence of label noise (2021) (5)
Sparse approximations for kernel learning vector quantization (2013) (5)
How to Quantitatively Compare Data Dissimilarities for Unsupervised Machine Learning? (2012) (5)
A probability theoretic approach to drifting data in continuous time domains (2019) (5)
Ages of the Avant-Garde (2018) (5)
Efficient metric learning for the analysis of motion data (2015) (5)
Supervised learning in the presence of concept drift: a modelling framework (2020) (5)
Matrix adaptation in discriminative vector quantization (2008) (5)
Let's go to the Alien Zoo: Introducing an experimental framework to study usability of counterfactual explanations for machine learning (2022) (5)
A General Framework for Self-Organizing Structure Processing Neural Networks (2003) (5)
Magnification Control in Relational Neural Gas (2008) (5)
Automatic discovery of metagenomic structure (2015) (5)
Efficient computation of counterfactual explanations and counterfactual metrics of prototype-based classifiers (2021) (5)
5th Workshop on Self-Organizing Maps : Paris 1 Panthéon-Sorbonne University 5th-8th September 2005 : proceedings (2005) (5)
FRI-Feature Relevance Intervals for Interpretable and Interactive Data Exploration (2019) (5)
Confident Kernel Sparse Coding and Dictionary Learning (2018) (5)
Adversarial Robustness Curves (2019) (5)
Fuzzy Labeled Self-Organizing Map for Classification of Spectra (2007) (5)
Supervised dimension reduction mappings (2011) (5)
Fast Non-Parametric Conditional Density Estimation using Moment Trees (2021) (5)
Towards an Automatic Analysis of CHO-K1 Suspension Growth in Microfluidic Single-cell Cultivation (2020) (5)
Certainty-based prototype insertion/deletion for classification with metric adaptation (2015) (5)
Machine Learning and Soft-Computing in Bioinformatics. A Short Journey (2006) (5)
Prototype Based Classification Using Information Theoretic Learning (2006) (5)
Unsupervised Dimensionality Reduction for Transfer Learning (2015) (5)
Visualizing Dissimilarity Data Using Generative Topographic Mapping (2010) (4)
Contrastive Explanations for Explaining Model Adaptations (2021) (4)
Application of Graph Convolutions in a Lightweight Model for Skeletal Human Motion Forecasting (2021) (4)
Determining Relevant Input Dimensions for the Self Organizing Map (2003) (4)
Using Nonlinear Dimensionality Reduction to Visualize Classifiers (2013) (4)
Supervised Neural Gas for Functional Data and its Application to the Analysis of Clinical Proteom Spectra (2007) (4)
Input pruning for neural gas architectures (2001) (4)
On the Generalization Ability of Recurrent Networks (2001) (4)
Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information (2019) (4)
Similarity-based Clustering and its Application to Medicine and Biology, 25.03. - 30.03.2007 (2007) (4)
Equilibrium Properties of Offline LVQ (2009) (4)
An EM transfer learning algorithm with applications in bionic hand prostheses (2017) (4)
A mathematical characterization of the architectural bias of recursive models (2004) (4)
Intuitive Clustering of Biological Data (2007) (4)
Accelerating kernel clustering for biomedical data analysis (2011) (4)
Nonlinear Dimension Reduction and Visualization of Labeled Data (2009) (4)
Efficient computation of contrastive explanations (2020) (4)
Perspectives and challenges for recurrent neural network training (2010) (4)
Clustering Very Large Dissimilarity Data Sets (2010) (4)
Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement Units (2019) (4)
Median Variant of Fuzzy c-Means (2009) (4)
Parallelizing single pass patch clustering (2008) (4)
Local Reject Option for Deterministic Multi-class SVM (2016) (4)
Approximation and generalization issues of recurrent networks dealing with structured data (2000) (4)
Probabilistic extension and reject options for pairwise LVQ (2017) (4)
Thinning Mesh Animations (2008) (4)
Accelerating dissimilarity clustering for biomedical data analysis (2011) (4)
Convergence of Multi-pass Large Margin Nearest Neighbor Metric Learning (2016) (4)
Concept Drift Segmentation via Kolmogorov-Trees (2021) (4)
Suitability of Different Metric Choices for Concept Drift Detection (2022) (4)
Agnostic Explanation of Model Change based on Feature Importance (2022) (4)
Discriminative dimensionality reduction for regression problems using the Fisher metric (2015) (3)
Applications of Discriminative Dimensionality Reduction (2013) (3)
Robust Centroid-Based Clustering using Derivatives of Pearson Correlation (2008) (3)
Efficient Adaptation of Structure Metrics in Prototype-Based Classification (2014) (3)
Federated Learning Vector Quantization (2021) (3)
Autonomous Learning of Representations (2015) (3)
Analysis of Spectral Data in Clinical Proteomics by Use of Learning Vector Quantizers (2008) (3)
Topographic Processing of Very Large Text Datasets (2008) (3)
Recovering Localized Adversarial Attacks (2019) (3)
Brain-inspired computing and machine learning (2020) (3)
Global Coordination Based on Matrix Neural Gas for Dynamic Texture Synthesis (2010) (3)
Optimum Reject Options for Prototype-based Classification (2015) (3)
About Learning of Supervised Generative Models for Dissimilarity Data (2013) (3)
Task-Sensitive Concept Drift Detector with Constraint Embedding (2021) (3)
Learning recursive data is intractable (1997) (3)
Preface: Intelligent interactive data visualization (2013) (3)
Contrasting Explanation of Concept Drift (2022) (3)
Relevance learning for mental disease classification (2005) (3)
On the generalization ability of GRLVQ (2003) (3)
Secure Semi-supervised Vector Quantization for Dissimilarity Data (2013) (3)
On the dynamics of Vector Quantization and Neural Gas (2007) (3)
Patch Affinity Propagation (2011) (3)
Effects of variability in synthetic training data on convolutional neural networks for 3D head reconstruction (2017) (2)
Explaining Reject Options of Learning Vector Quantization Classifiers (2022) (2)
“Even if …” – Diverse Semifactual Explanations of Reject (2022) (2)
Intuitiveness in Active Teaching (2020) (2)
Contrasting Explanations for Understanding and Regularizing Model Adaptations (2022) (2)
On the capacity of unsupervised recursive neural networks for symbol processing (2006) (2)
Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams (2022) (2)
On the Identification of Decision Boundaries for Anomaly Detection in CPPS (2019) (2)
Learning Vector Quantization Classification with Local Relevance Determination for Medical Data (2006) (2)
Relevance determination in reinforcement learning (2005) (2)
AutoML Technologies for the Identification of Sparse Models (2021) (2)
Vector Quantization with Rule Extraction for Mixed Domain Data (2002) (2)
Drift Detection in Text Data with Document Embeddings (2021) (2)
Stream-based Active Learning with Verification Latency in Non-stationary Environments (2022) (2)
Perspectives of Self-adapted Self-organizing Clustering in Organic Computing (2006) (2)
Automated Contamination Detection in Single-Cell Sequencing (2015) (2)
Taking Care of Our Drinking Water: Dealing with Sensor Faults in Water Distribution Networks (2022) (2)
Metric adaptation and relevance learning in learning vector quantization (2003) (2)
Discriminative Dimensionality Reduction for the Visualization of Classifiers (2013) (2)
Reservoir Memory Machines as Neural Computers (2020) (2)
Sparse representation of data (2010) (2)
Relevance Learning for Dimensionality Reduction (2014) (2)
Workshop New Challenges in Neural Computation (2011) (2)
How to evaluate Dimensionality Reduction (technical report) (2011) (2)
Relevance learning for short high-dimensional time series in the life sciences (2012) (2)
DeepView: Visualizing the behavior of deep neural networks in a part of the data space (2019) (2)
Echo State Networks as Novel Approach for Low-Cost Myoelectric Control (2017) (2)
Interpretable Locally Adaptive Nearest Neighbors (2020) (2)
Aggregation of multiple peak lists by use of an improved neural gas network (2007) (2)
An Interview with Barbara Hammer (1998) (2)
Relevance learning for time series inspection (2012) (2)
Closure properties of uniform convergence of empirical means and PAC learnability under a family of probability measures (2001) (2)
Single Pass Clustering and Classification of Large Dissimilarity Datasets (2008) (2)
Non-Negative Quadratic Pursuit (2018) (2)
Explainable Artificial Intelligence for Improved Modeling of Processes (2022) (2)
Accelerating Kernel Neural Gas (2011) (2)
Limitations of hybrid systems (2000) (2)
A Shape-Based Method for Concept Drift Detection and Signal Denoising (2021) (1)
Mapping the Design Space of Reinforcement Learning Problems - a Case Study (2004) (1)
Paris Self-Organizing Maps for Time Series (2005) (1)
Neural networks classifying symbolic data (2000) (1)
Discriminative dimensionality reduction in kernel space (2016) (1)
Sequential Feature Classification in the Context of Redundancies (2020) (1)
Proc. 6th International Workshop on Self-Organizing Maps (2007) (1)
Linear Time Heuristics for Topographic Mapping of Dissimilarity Data (2011) (1)
Metric adaptation for optimal feature classification in learning vector quantization applied to environment detection (2004) (1)
Equilibrium properties of off-line LVQ (2009) (1)
On the suitability of incremental learning for regression tasks in exoskeleton control (2021) (1)
09081 Summary - Similarity-based learning on structures (2009) (1)
Novel transfer learning schemes based on Siamese networks and synthetic data (2022) (1)
A reinforcement learning algorithm to improve scheduling search heuristics with the SVM (2004) (1)
BERT WEAVER: Using WEight AVERaging to Enable Lifelong Learning for Transformer-based Models (2022) (1)
Linear supervised transfer learning for the large margin nearest neighbor classifier (2017) (1)
Fairness and Robustness of Contrasting Explanations (2021) (1)
Metric Learning in Dimensionality Reduction (2015) (1)
Visualizing dependencies of spectral features using mutual information (2013) (1)
Analysis of Drifting Features (2020) (1)
Locally Adaptive Nearest Neighbors (2020) (1)
Similarity-based learning on structures (2009) (1)
A NP-hardness result for a sigmoidal 3-node neural network (1997) (1)
Inferring Temporal Structure from Predictability in Bumblebee Learning Flight (2018) (1)
Relational Clustering (2007) (1)
Deep-Aligned Convolutional Neural Network for Skeleton-Based Action Recognition and Segmentation (2020) (1)
Editorial: A Successful Year and Looking Forward to 2017 and Beyond (2017) (1)
Time integration and reject options for probabilistic output of pairwise LVQ (2020) (1)
Using Discriminative Dimensionality Reduction to Visualize Classifiers (2014) (1)
Efficient Reject Options for Particle Filter Object Tracking in Medical Applications (2021) (1)
Non-Negative Kernel Sparse Coding for the Classification of Motion Data (2019) (1)
Autonomous Learning of Representations (2015) (1)
19th European Symposium on Artificial Neural Networks, ESANN 2011, Bruges, Belgium, April 27-29, 2011, Proceedings (2011) (1)
Similarity based clustering and its application to medicine and biology : 07131 abstracts collection ; Dagstuhl seminar (2007) (1)
Some steps towards a general principle for dimensionality reduction mappings (2010) (1)
Interpretable Multiple-Kernel Prototype Learning for Discriminative Representation and Feature Selection (2019) (1)
Non-negative Local Sparse Coding for Subspace Clustering (2018) (1)
Soft Competitive Learning for Large Data Sets (2012) (1)
One Explanation to Rule them All - Ensemble Consistent Explanations (2022) (1)
Artificial Neural Networks and Machine Learning – ICANN 2018 (2018) (1)
Randomizing the Self-Adjusting Memory for Enhanced Handling of Concept Drift (2020) (1)
Explaining Concept Drift by Mean of Direction (2020) (1)
Label-noise-tolerant classification for streaming data (2017) (1)
Dedicated Memory Models for Continual Learning in the Presence of Concept Drift (2016) (1)
Online metric learning for an adaptation to confidence drift (2016) (1)
Chapter 15 - Neural Networks (2014) (1)
Prototype-based Models for the Supervised Learning of Classification Schemes (2016) (1)
Feasibility based Large Margin Nearest Neighbor metric learning (2016) (1)
Differential private relevance learning (2018) (1)
Performance analysis of LVQ algorithms (2006) (1)
Sparse Prototype Representation by Core Sets (2013) (1)
Class imaging of hyperspectral satellite remote sensing data using FLSOM (2007) (1)
Beyond the Coffeehouse (2007) (1)
Large-Margin Multiple Kernel Learning for Discriminative Features Selection and Representation Learning (2019) (1)
Discriminative probabilistic prototype based models in kernel space (2012) (1)
Barbara Hammer; Filmmaker (1998) (1)
Analysis of Proteomic Spectral Data by Multi Resolution Analysis and Self-Organizing Maps (2007) (1)
Stomp for the Shadows (2013) (1)
Localization of Concept Drift: Identifying the Drifting Datapoints (2022) (1)
The SAME score: Improved cosine based bias score for word embeddings (2022) (1)
Model Agnostic Local Explanations of Reject (2022) (1)
"Explain it in the Same Way!" - Model-Agnostic Group Fairness of Counterfactual Explanations (2022) (1)
Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data (2022) (1)
SAM-kNN Regressor for Online Learning in Water Distribution Networks (2022) (1)
A Graph-based U-Net Model for Predicting Traffic in unseen Cities (2022) (1)
Patch Processing for Relational Learning Vector Quantization (2012) (1)
Time Series Prediction for Graphs in Kernel and Dissimilarity Spaces (2017) (1)
Development of a Novel Media-independent Communication Theology for Accessing Local & Web-based Data: Case Study with Robotic Sub- systems (2021) (0)
Combining self-labeling and demand based active learning for non-stationary data streams (2023) (0)
Learning in the Loop : Fast Explorative Learning of Inverse Models in High Dimensions (0)
Multiple-Kernel Dictionary Learning for Sparse Reconstruction of Unseen Multivariate Time-series ? (2018) (0)
Recurrent and folding networks (2000) (0)
68 11341 – Learning in the context of very high dimensional data 1 Executive Summary (2011) (0)
Neural Information Processing (2013) (0)
Proc. 13th Symposium on Artificial Neural Networks (ESANN 2005) (2005) (0)
On Early Stages of Learning in Connectionist Models with Feedback Connections (2004) (0)
Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008 (2008) (0)
Unsupervised Unlearning of Concept Drift with Autoencoders (2022) (0)
13th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems, ATMOS 2013, September 5, 2013, Sophia Antipolis, France (2013) (0)
On the Hardness and Necessity of Supervised Concept Drift Detection (2023) (0)
Bounds for Ordinal Regression Pfannschmidt (2019) (0)
VI Self-Organizing Maps and Learning Vector Quantization for Complex Data (2015) (0)
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams (2023) (0)
18th European Symposium on Artificial Neural Networks, ESANN 2010, Bruges, Belgium, April 28-30, 2010, Proceedings (2010) (0)
8 Metric Learning for Prototype-Based Classification (0)
08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications (2008) (0)
Task-Driven Sparse Coding for Classification of Motion Data (2017) (0)
of Learning ( in a nutshell ) (2018) (0)
Supervised learning in the presence of concept drift: a modelling framework (2021) (0)
Visualizing classifiers of proximity data (2018) (0)
University of Groningen Functional relevance learning in generalized learning vector quantization (2017) (0)
Analyzing Feature Relevance for Linear Reject Option SVM using Relevance Intervals (2017) (0)
Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings (2021) (0)
Debiasing Sentence Embedders Through Contrastive Word Pairs (2023) (0)
Reservoir Stack Machines (2021) (0)
Supervised learning of short and high-dimensional temporal sequences for life science measurements (2011) (0)
Metric Learning with Self-Adjusting Memory for Explaining Feature Drift (2023) (0)
Echo State Networks for Low-Cost Myoelectric Prosthesis Control (2017) (0)
Workshop of the GI-Fachgruppe Neuronale Netze and the German Neural Networks Society in connection to DAGM 2012 (2012) (0)
Non-negative Kernel Sparse Coding Frameworks for Efficient Analysis of Motion Data (2017) (0)
ICOLE 2008, Lessach, Austria (2008) (0)
Pattern Recognition by Supervised Relevance Neural Gas and its Application to Spectral Data in Bioinformatics (2008) (0)
Relevance learning in generative topographic maps (2010) (0)
Regression Problems using the Fisher Metric (2015) (0)
Prototype Based Classification in Bioinformatics (2009) (0)
Sparse conformal prediction for dissimilarity data (2014) (0)
Spatial Graph Convolution Neural Networks for Water Distribution Systems (2022) (0)
Automated generation of classifier based monitoring functions and its application to automotive steering control (2010) (0)
University of Groningen Equilibrium Properties of Offline LVQ (2017) (0)
PerformanceAnalysisofLVQAlgorithms:AStatistical PhysicsApproach (2006) (0)
Special Issue on Neural Learning Paradigms (2012) (0)
07131 Summary -- Similarity-based Clustering and its Application to Medicine and Biology (2007) (0)
Special issue on new challenges in neural computation 2012 (2014) (0)
Visualization of Regression Models Using Discriminative Dimensionality Reduction (2015) (0)
A general framework for unsupervisedprocessing of structuredd ata (2004) (0)
Proc. 5th Intl. Workshop on Self-Organising Maps (WSOM 2005) (2005) (0)
Classi fi cation of MRI Migraine Medical Data using 3 D Convolutional Neural Network � (0)
Special Issue on Autonomous Learning (2015) (0)
Precise Change Point Detection using Spectral Drift Detection (2022) (0)
Special Issue on Neural Learning Paradigms (2012) (0)
Workshop New Challenges in Neural Computation 2010 (2010) (0)
"Art Is Energy": Barbara Hammer Speaks with Sarah Keller about the State of Experimental Cinema after Maya Deren (2017) (0)
Preface: Intelligent interactive data visualization (2013) (0)
Art Cart: Honoring the Legacy HD (2016) (0)
Challenges in Neural Computation (2012) (0)
Belief (2012) (0)
University of Groningen Generalized Derivative Based Kernelized Learning Vector Quantization Schleif, (2010) (0)
New Aspects in Neurocomputing (2005) (0)
Development of a Novel Media-independent (2021) (0)
Lover other. The story of Claude Cahun and Marcel Moore: The Female closet (2018) (0)
Evaluating Metrics for Bias in Word Embeddings (2021) (0)
17th European Symposium on Artificial Neural Networks, ESANN 2009, Bruges, Belgium, April 22-24, 2009, Proceedings (2009) (0)
Media Review: Students with Asperger Syndrome: A Guide for College Personnel (2012) (0)
Honoring the Legacy: an Exhibition of Works Presented by ART CART: SAVING THE LEGACY (2016) (0)
OPEN LETTER TO THE EXPERIMENTAL FILM CONGRESS: LET’S SET THE RECORD STRAIGHT (Canada, 1989) (2019) (0)
The eMINTS Project: Enhancing Missouri's Instructional Networked Teaching Strategies -- Promising Developments and Projected Outcomes (2000) (0)
Brain-Inspired Computing, International Workshop, Cetraro/Italy, July 2013 (2014) (0)
Barbara Hammer: Catalog of Works and Images (2016) (0)
The Complexity of Learning with Supportvector Machines — A Statistical Physics Study (2003) (0)
ICOLE 2009, Lessach, Austria (2009) (0)
COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS (2009) (0)
From hyperspectral to multispectral sensing – from simulation to reality: A comprehensive approach for calibration model transfer (2022) (0)
Brain-inspired computing and machine learning (2020) (0)
Federated learning vector quantization for dealing with drift between nodes (2022) (0)
IEEE CIDM 2011 Committee Symposium on Computational Intelligence and Data Mining (IEEE CIDM 2011) (2011) (0)
Voxel-Based Three-Dimensional Neural Style Transfer (2021) (0)
Improving Zorro Explanations for Sparse Observations with Dense Proxy Data (2022) (0)
Time integration and reject options for probabilistic output of pairwise LVQ (2019) (0)
Dimension Reduction and Visualization of Labeled Data (2009) (0)
Neural gas clustering for sparse proximity data (2007) (0)
On the Change of Decision Boundaries and Loss in Learning with Concept Drift (2022) (0)
Machine Learning for Measuring and Analyzing Online Social Communications (2021) (0)
Fuzzy Classification for Classification of Mass Spectrometric Data Based on Learning Vector Quantization (2005) (0)
Model Based Explanations of Concept Drift (2023) (0)
Reject Options for Incremental Regression Scenarios (2022) (0)
So Can We Use Intrinsic Bias Measures or Not? (2023) (0)
07131 Abstracts Collection -- Similarity-based Clustering and its Application to Medicine and Biology (2007) (0)
Best of both, Structured and Unstructured Sparsity in Neural Networks (2023) (0)
AutoML technologies for the identification of sparse classification and outlier detection models (2022) (0)
Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams (2023) (0)
ICOLE 2007, Lessach, Austria (2007) (0)
Classifier inspection based on different discriminative dimensionality reductions (2013) (0)
Learning paradigms in dynamic environments (2010) (0)
Efficient Sensor Selection for Individualized Prediction Based on Biosignals (2022) (0)
Multiple-Kernel dictionary learning for reconstruction and clustering of unseen multivariate time-series (2019) (0)
Virtual optimisation for improved production planning (2016) (0)
Intelligent Learning Rate Distribution to Reduce Catastrophic Forgetting in Transformers (2022) (0)
10302 Abstracts Collection - Learning paradigms in dynamic environments (2010) (0)
Interpretation of linear mappings employing L1 regularization (2014) (0)
Odor recognition in robotics applications by discriminative time-series modeling (2015) (0)
Unsupervised Cyclic Siamese Networks Automating Cell Imagery Analysis (2023) (0)
Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM) (2017) (0)
Sparse Metric Learning in Prototype-based Classification (2020) (0)
MIWOCI Workshop 2014 (2014) (0)
University of Groningen Feature Relevance Bounds for Ordinal Regression Pfannschmidt (2019) (0)
Single-Step Adversarial Training for Semantic Segmentation (2021) (0)
Report from Dagstuhl Seminar 14381 Neural-Symbolic Learning and Reasoning (2015) (0)
On the generalization ability of simple recurrent neural networks (1997) (0)
New Challenges in Neural Computation NC 2 – 2010 (2016) (0)
10302 Summary - Learning paradigms in dynamic environments (2010) (0)
University of Groningen Equilibrium Properties of Offline (2018) (0)
Feature Selection for Trustworthy Regression Using Higher Moments (2022) (0)
ICOLE-2007, German-Polish Workshop on Computational Biology, Scheduling and Machine Learning. Lessach, Austria, 27.05.-02.06.2007 (2007) (0)
Modularity in Nervous Systems—a Key to Efficient Adaptivity for Deep Reinforcement Learning (2023) (0)
08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications (2008) (0)
09081 Abstracts Collection - Similarity-based learning on structures (2009) (0)
SHAP-IQ: Unified Approximation of any-order Shapley Interactions (2023) (0)
"Why Here and Not There?" - Diverse Contrasting Explanations of Dimensionality Reduction (2022) (0)
Neural Architecture Search for Sentence Classification with BERT (2022) (0)

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