Andrej Gisbrecht - researchr alias

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Viewing Publication 1 - 40 from 40

2022

Graph Representation and Embedding for Semiconductor Manufacturing Fab StatesBenedikt Schulz, Christoph Jacobi, Andrej Gisbrecht, Angelidis Evangelos, Chew Wye Chan, Boon-Ping Gan. wsc 2022: 3382-3393 [doi]

2018

Supervised low rank indefinite kernel approximation using minimum enclosing ballsFrank-Michael Schleif, Andrej Gisbrecht, Peter Tiño. ijon, 318:213-226, 2018. [doi]

2015

Advances in dissimilarity-based data visualisationAndrej Gisbrecht. PhD thesis, Universität Bielefeld, 2015. [doi]

Metric and non-metric proximity transformations at linear costsAndrej Gisbrecht, Frank-Michael Schleif. ijon, 167:643-657, 2015. [doi]

Data visualization by nonlinear dimensionality reductionAndrej Gisbrecht, Barbara Hammer. widm, 5(2):51-73, 2015. [doi]

Parametric nonlinear dimensionality reduction using kernel t-SNEAndrej Gisbrecht, Alexander Schulz, Barbara Hammer. ijon, 147:71-82, 2015. [doi]

Efficient approximations of robust soft learning vector quantization for non-vectorial dataDaniela Hofmann, Andrej Gisbrecht, Barbara Hammer. ijon, 147:96-106, 2015. [doi]

Probabilistic Classification Vector Machine at large scaleFrank-Michael Schleif, Andrej Gisbrecht, Peter Tiño. esann 2015: [doi]

Large Scale Indefinite Kernel Fisher DiscriminantFrank-Michael Schleif, Andrej Gisbrecht, Peter Tiño. simbad 2015: 160-170 [doi]

Using Discriminative Dimensionality Reduction to Visualize ClassifiersAlexander Schulz, Andrej Gisbrecht, Barbara Hammer. npl, 42(1):27-54, 2015. [doi]

2014

Innovationen für die distanzbasierte DatenvisualisierungAndrej Gisbrecht. gi 2015: 81-90

Relevance Learning for Dimensionality ReductionAlexander Schulz, Andrej Gisbrecht, Barbara Hammer. esann 2014: [doi]

2013

Discriminative Dimensionality Reduction for the Visualization of ClassifiersAndrej Gisbrecht, Alexander Schulz, Barbara Hammer. icpram 2015: 39-56 [doi]

Visualizing dependencies of spectral features using mutual informationAndrej Gisbrecht, Yoan Miché, Barbara Hammer, Amaury Lendasse. esann 2013: [doi]

Nonlinear Dimensionality Reduction for Cluster Identification in Metagenomic SamplesAndrej Gisbrecht, Barbara Hammer, Bassam Mokbel, Alexander Sczyrba. IV 2013: 174-179 [doi]

Applications of Discriminative Dimensionality ReductionBarbara Hammer, Andrej Gisbrecht, Alexander Schulz. icpram 2013: 33-41

Visualizing the quality of dimensionality reductionBassam Mokbel, Wouter Lueks, Andrej Gisbrecht, Barbara Hammer. ijon, 112:109-123, 2013. [doi]

Data Analysis of (Non-)Metric Proximities at Linear CostsFrank-Michael Schleif, Andrej Gisbrecht. simbad 2013: 59-74 [doi]

Using Nonlinear Dimensionality Reduction to Visualize ClassifiersAlexander Schulz, Andrej Gisbrecht, Barbara Hammer. iwann 2013: 59-68 [doi]

2012

Out-of-sample kernel extensions for nonparametric dimensionality reductionAndrej Gisbrecht, Wouter Lueks, Bassam Mokbel, Barbara Hammer. esann 2012: [doi]

Relevance learning for time series inspectionAndrej Gisbrecht, Dusan Sovilj, Barbara Hammer, Amaury Lendasse. esann 2012: [doi]

Linear basis-function t-SNE for fast nonlinear dimensionality reductionAndrej Gisbrecht, Bassam Mokbel, Barbara Hammer. ijcnn 2012: 1-8 [doi]

Discriminative Dimensionality Reduction MappingsAndrej Gisbrecht, Daniela Hofmann, Barbara Hammer. ida 2012: 126-138 [doi]

Linear Time Relational Prototype Based LearningAndrej Gisbrecht, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu, Barbara Hammer. IJNS, 22(5), 2012. [doi]

How to Visualize Large Data Sets?Barbara Hammer, Andrej Gisbrecht, Alexander Schulz. wsom 2013: 1-12 [doi]

Efficient Approximations of Kernel Robust Soft LVQDaniela Hofmann, Andrej Gisbrecht, Barbara Hammer. wsom 2013: 183-192 [doi]

Visualizing the quality of dimensionality reductionBassam Mokbel, Wouter Lueks, Andrej Gisbrecht, Michael Biehl, Barbara Hammer. esann 2012: [doi]

Relevance learning for short high-dimensional time series in the life sciencesFrank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer. ijcnn 2012: 1-8 [doi]

Learning Relevant Time Points for Time-Series Data in the Life SciencesFrank-Michael Schleif, Bassam Mokbel, Andrej Gisbrecht, Leslie Theunissen, Volker Dürr, Barbara Hammer. icann 2012: 531-539 [doi]

Fast approximated relational and kernel clusteringFrank-Michael Schleif, Xibin Zhu, Andrej Gisbrecht, Barbara Hammer. icpr 2012: 1229-1232 [doi]

Approximation techniques for clustering dissimilarity dataXibin Zhu, Andrej Gisbrecht, Frank-Michael Schleif, Barbara Hammer. ijon, 90:72-84, 2012. [doi]

2011

Linear Time Heuristics for Topographic Mapping of Dissimilarity DataAndrej Gisbrecht, Frank-Michael Schleif, Xibin Zhu, Barbara Hammer. ideal 2011: 25-33 [doi]

Accelerating kernel clustering for biomedical data analysisAndrej Gisbrecht, Barbara Hammer, Frank-Michael Schleif, Xibin Zhu. cibcb 2011: 154-161 [doi]

Relevance learning in generative topographic mappingAndrej Gisbrecht, Barbara Hammer. ijon, 74(9):1351-1358, 2011. [doi]

Relational generative topographic mappingAndrej Gisbrecht, Bassam Mokbel, Barbara Hammer. ijon, 74(9):1359-1371, 2011. [doi]

Topographic Mapping of Dissimilarity DataBarbara Hammer, Andrej Gisbrecht, Alexander Hasenfuss, Bassam Mokbel, Frank-Michael Schleif, Xibin Zhu. wsom 2011: 1-15 [doi]

Accelerating Kernel Neural GasFrank-Michael Schleif, Andrej Gisbrecht, Barbara Hammer. icann 2011: 150-158 [doi]

2010

Relational Generative Topographic MapAndrej Gisbrecht, Bassam Mokbel, Barbara Hammer. esann 2010: [doi]

Relevance learning in generative topographic mapsAndrej Gisbrecht, Barbara Hammer. esann 2010: [doi]

Visualizing Dissimilarity Data Using Generative Topographic MappingAndrej Gisbrecht, Bassam Mokbel, Alexander Hasenfuss, Barbara Hammer. ki 2010: 227-237 [doi]

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