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Differential privacy for learning vector quantization
Brinkrolf, Johannes ; Göpfert, Christina ; Hammer, Barbara
In: Neurocomputing, Jg. 342, S. 125-136
2019
Discriminative Dimensionality Reduction in Kernel Space
Schulz, Alexander ; Hammer, Barbara
2016
Discriminative dimensionality reduction: variations, applications, interpretations
Schulz, Alexander
2017
Dissimilarity-based learning for complex data
Mokbel, Bassam
2016
Effects of Variability in Synthetic Training Data on Convolutional Neural Networks for 3D Head Reconstruction
Göpfert, Jan Philip ; Göpfert, Christina ; Botsch, Mario ; Hammer, Barbara
2017
Efficient Grouping Methods for the Annotation and Sorting of Single Cells
Lux, Markus
2018
Efficient Kernelization of Discriminative Dimensionality Reduction
Schulz, Alexander ; Brinkrolf, Johannes ; Hammer, Barbara
In: Neurocomputing, Jg. 268 H. SI, S. 34-41
2017
Feature Relevance Bounds for Linear Classification
Göpfert, Christina ; Pfannschmidt, Lukas ; Hammer, Barbara ; Verleysen, Michele (Hrsg.)
2017
FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration
Pfannschmidt, Lukas ; Göpfert, Christina ; Neumann, Ursula ; Heider, Dominik ; Hammer, Barbara
2019
Gaussian process prediction for time series of structured data
Paaßen, Benjamin ; Göpfert, Christina ; Hammer, Barbara ; Verleysen, Michele (Hrsg.)
2016
Incremental on-line learning: A review and comparison of state of the art algorithms
Losing, Viktor ; Hammer, Barbara ; Wersing, Heiko
In: Neurocomputing, Jg. 275, S. 1261-1274
2018
Inferring Feature Relevances From Metric Learning
Schulz, Alexander ; Mokbel, Bassam ; Biehl, Michael ; Hammer, Barbara
2015
Interactive Online Learning for Obstacle Classification on a Mobile Robot
Losing, Viktor ; Hammer, Barbara ; Wersing, Heiko
2015
Interpretation of Linear Classifiers by Means of Feature Relevance Bounds
Göpfert, Christina ; Pfannschmidt, Lukas ; Göpfert, Jan Philip ; Hammer, Barbara
In: Neurocomputing, Jg. 298, S. 69-79
2018
KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift
Losing, Viktor ; Hammer, Barbara ; Wersing, Heiko
2016
Learning Feedback in Intelligent Tutoring Systems
Gross, Sebastian ; Mokbel, Bassam ; Hammer, Barbara ; Pinkwart, Niels
In: KI - Künstliche Intelligenz, Jg. 29 H. 4, S. 1-6
2015
Learning vector quantization for proximity data
Hofmann, Daniela
2016
Lecture Notes on Applied Optimization
Paaßen, Benjamin ; Artelt, André ; Hammer, Barbara
2019
Memory Models for Incremental Learning Architectures
Losing, Viktor
2019
Metric learning for sequences in relational LVQ
Mokbel, Bassam ; Paaßen, Benjamin ; Schleif, Frank-Michael ; Hammer, Barbara
In: Neurocomputing, Jg. 169 H. SI, S. 306-322
2015
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63 Titel
Klassifikation
Schliessen
Filter
4

Differential privacy for learning vector quantization

Discriminative Dimensionality Reduction in Kernel Space

Discriminative dimensionality reduction: variations, applications, interpretations

Dissimilarity-based learning for complex data

Effects of Variability in Synthetic Training Data on Convolutional Neural Networks for 3D Head Reconstruction

Efficient Grouping Methods for the Annotation and Sorting of Single Cells

Efficient Kernelization of Discriminative Dimensionality Reduction

Feature Relevance Bounds for Linear Classification

FRI - Feature Relevance Intervals for Interpretable and Interactive Data Exploration

Gaussian process prediction for time series of structured data

Incremental on-line learning: A review and comparison of state of the art algorithms

Inferring Feature Relevances From Metric Learning

Interactive Online Learning for Obstacle Classification on a Mobile Robot

Interpretation of Linear Classifiers by Means of Feature Relevance Bounds

KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift

Learning Feedback in Intelligent Tutoring Systems

Learning vector quantization for proximity data

Lecture Notes on Applied Optimization

Memory Models for Incremental Learning Architectures

Metric learning for sequences in relational LVQ

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63 Titel
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