33 Publikationen

Alle markieren

[33]
2020 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2944327
Panda A, Yadav A, Yeerna H, Singh A, Biehl M, Lux M, Schulz A, Klecha T, Doniach S, Khiabanian H, Ganesan S, Tamayo P, Bhanot G (2020)
Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples.
Nucleic acids research.
PUB | DOI | PubMed | Europe PMC
 
[32]
2020 | Konferenzbeitrag | PUB-ID: 2943260
Schulz A, Hinder F, Hammer B (2020)
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction.
In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, {IJCAI-20}. .
PUB | DOI | Download (ext.)
 
[31]
2020 | Konferenzbeitrag | Im Druck | PUB-ID: 2941931
Paaßen B, Schulz A (In Press)
Reservoir memory machines.
In: Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). Verleysen M (Ed); Bruges.
PUB | Download (ext.) | arXiv
 
[30]
2019 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2934458 OA
Prahm C, Schulz A, Paaßen B, Schoisswohl J, Kaniusas E, Dorffner G, Hammer B, Aszmann O (2019)
Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning.
IEEE Transactions on Neural Systems and Rehabilitation Engineering 27(5): 956-962.
PUB | PDF | DOI | WoS | PubMed | Europe PMC
 
[29]
2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914505
Paaßen B, Schulz A, Hahne J, Hammer B (2018)
Expectation maximization transfer learning and its application for bionic hand prostheses.
Neurocomputing 298: 122-133.
PUB | DOI | Download (ext.) | WoS | arXiv
 
[28]
2018 | Konferenzbeitrag | PUB-ID: 2930001 OA
Schulz A, Queißer J, Ishihara H, Asada M (2018)
Transfer Learning of Complex Motor Skills on the Humanoid Robot Affetto.
Presented at the International Conference on Development and Learning and on Epigenetic Robotics 2018 (ICDL-EPIROB2018), Tokyo (In Press).
PUB | PDF
 
[27]
2018 | Konferenzbeitrag | PUB-ID: 2916318
Berger K, Schulz A, Paaßen B, Hammer B (2018)
Linear Supervised Transfer Learning for the Large Margin Nearest Neighbor Classifier.
Presented at the SSCI CIDM 2017.
PUB | DOI
 
[26]
2017 | Datenpublikation | PUB-ID: 2912671 OA
Paaßen B, Schulz A (2017)
Linear Supervised Transfer Learning Toolbox.
Bielefeld University.
PUB | Dateien verfügbar | DOI
 
[25]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909369 OA
Paaßen B, Schulz A, Hahne J, Hammer B (2017)
An EM transfer learning algorithm with applications in bionic hand prostheses.
In: Proceedings of the 25th European Symposium on Artificial Neural Networks (ESANN 2017). Verleysen M (Ed); Bruges: i6doc.com: 129-134.
PUB | PDF
 
[24]
2017 | Bielefelder E-Dissertation | PUB-ID: 2914256 OA
Schulz A (2017)
Discriminative dimensionality reduction: variations, applications, interpretations.
Bielefeld: Universität Bielefeld.
PUB | PDF
 
[23]
2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2909372 OA
Schulz A, Brinkrolf J, Hammer B (2017)
Efficient Kernelization of Discriminative Dimensionality Reduction.
Neurocomputing 268(SI): 34-41.
PUB | PDF | DOI | WoS
 
[22]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909037 OA
Prahm C, Schulz A, Paaßen B, Aszmann O, Hammer B, Dorffner G (2017)
Echo State Networks as Novel Approach for Low-Cost Myoelectric Control.
In: Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME 2017). ten Telje A, Popow C, Holmes JH, Sacchi L (Eds); Lecture Notes in Computer Science, 10259. Springer: 338--342.
PUB | Dateien verfügbar | DOI
 
[21]
2016 | Konferenzbeitrag | E-Veröff. vor dem Druck | PUB-ID: 2904909 OA
Schulz A, Hammer B (2016)
Discriminative Dimensionality Reduction in Kernel Space.
In: ESANN2016 Proceedings. 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium,27-29 April 2016. i6doc.com.
PUB | PDF
 
[20]
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905855
Paaßen B, Schulz A, Hammer B (2016)
Linear Supervised Transfer Learning for Generalized Matrix LVQ.
In: Proceedings of the Workshop New Challenges in Neural Computation 2016. Hammer B, Martinetz T, Villmann T (Eds); Machine Learning Reports, 11-18.
PUB | Download (ext.)
 
[19]
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904178 OA
Prahm C, Paaßen B, Schulz A, Hammer B, Aszmann O (2016)
Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis after Electrode Shift.
In: Converging Clinical and Engineering Research on Neurorehabilitation II: Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016). Ibáñez J, Gonzáles-Vargas J, Azorín JM, Akay M, Pons JL (Eds); Springer: 153--157.
PUB | PDF | DOI | Download (ext.)
 
[18]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2671047 OA
Gisbrecht A, Schulz A, Hammer B (2015)
Parametric nonlinear dimensionality reduction using kernel t-SNE.
Neurocomputing 147: 71-82.
PUB | PDF | DOI | WoS
 
[17]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2903777 OA
Schulz A, Mokbel B, Biehl M, Hammer B (2015)
Inferring Feature Relevances From Metric Learning.
In: 2015 IEEE Symposium Series on Computational Intelligence. Piscataway, NJ: IEEE.
PUB | PDF | DOI
 
[16]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2766822 OA
Schulz A, Gisbrecht A, Hammer B (2015)
Using Discriminative Dimensionality Reduction to Visualize Classifiers.
Neural Processing Letters 42(1): 27-54.
PUB | PDF | DOI | WoS
 
[15]
2015 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2900303 OA
Schulz A, Hammer B (2015)
Visualization of Regression Models Using Discriminative Dimensionality Reduction.
In: Computer Analysis of Images and Patterns. Lecture Notes in Computer Science, 9257. Cham: Springer Science + Business Media: 437-449.
PUB | PDF | DOI
 
[14]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900325 OA
Blöbaum P, Schulz A, Hammer B (2015)
Unsupervised Dimensionality Reduction for Transfer Learning.
In: Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen M (Ed); Louvain-la-Neuve: Ciaco: 507-512.
PUB | PDF
 
[13]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900319
Schulz A, Hammer B (2015)
Discriminative dimensionality reduction for regression problems using the Fisher metric.
In: 2015 International Joint Conference on Neural Networks (IJCNN). Institute of Electrical & Electronics Engineers (IEEE): 1-8.
PUB | DOI
 
[12]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2783369 OA
Mokbel B, Schulz A (2015)
Towards Dimensionality Reduction for Smart Home Sensor Data.
In: Proceedings of the Workshop New Challenges in Neural Computation (NC² 2015). Hammer B, Martinetz T, Villmann T (Eds); Machine Learning Reports, 41-48.
PUB | PDF | Download (ext.)
 
[11]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900318
Schulz A, Hammer B (2015)
Metric Learning in Dimensionality Reduction.
In: Proceedings of the International Conference on Pattern Recognition Applications and Methods. Scitepress: 232-239.
PUB | DOI
 
[10]
2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900320
Frenay B, Hofmann D, Schulz A, Biehl M, Hammer B (2014)
Valid interpretation of feature relevance for linear data mappings.
In: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Institute of Electrical & Electronics Engineers (IEEE): 149-156.
PUB | DOI
 
[9]
2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673557
Schulz A, Gisbrecht A, Hammer B (2014)
Relevance learning for dimensionality reduction.
In: ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen M (Ed); Bruges, Belgium: i6doc.com: 165-170.
PUB
 
[8]
2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900322
Bloebaum P, Schulz A (2014)
Transfer Learning without given Correspondences.
In: Proceedings of the Workshop New Challenges in Neural Computation (NC² 2014). Hammer B, Martinetz T, Villmann T (Eds); Machine Learning Reports, 42-51.
PUB
 
[7]
2014 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2900324
Gisbrecht A, Schulz A, Hammer B (2014)
Discriminative Dimensionality Reduction for the Visualization of Classifiers.
In: Pattern Recognition Applications and Methods. Advances in Intelligent Systems and Computing, 318. Cham: Springer Science + Business Media: 39-56.
PUB | DOI
 
[6]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622454
Hammer B, Gisbrecht A, Schulz A (2013)
Applications of discriminative dimensionality reduction.
In: Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods. SCITEPRESS: 33-41.
PUB | DOI
 
[5]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622456
Schulz A, Gisbrecht A, Hammer B (2013)
Using Nonlinear Dimensionality Reduction to Visualize Classifiers.
In: Advances in computational intelligence. Proceedings. Vol 1. Rojas I, Joya G, Gabestany J (Eds); Lecture Notes in Computer Science, 7902. Springer: 59-68.
PUB | DOI | WoS
 
[4]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622466
Vukanovicz S, Schulz A, Haschke R, Ritter H (2013)
Learning the Appropriate Model Population Structures for Locally Weighted Regression.
In: Workshop New Challenges in Neural Computation 2013. Machine Learning Reports, 2013. Bielefeld: Universität Bielefeld: 87.
PUB
 
[3]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622467
Schulz A, Gisbrecht A, Hammer B (2013)
Classifier inspection based on different discriminative dimensionality reductions.
In: Workshop NC^2 2013. TR Machine Learning Reports: 77-86.
PUB
 
[2]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622449
Schulz A, Gisbrecht A, Bunte K, Hammer B (2012)
How to visualize a classifier?
In: Proceedings of the Workshop - New Challenges in Neural Computation 2012. Machine Learning Reports: 73-83.
PUB
 
[1]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622453
Hammer B, Gisbrecht A, Schulz A (2012)
How to Visualize Large Data Sets?
Presented at the Workshop Advances in Self-Organizing Maps (WSOM), Santiago, Chile.
PUB | DOI
 

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Publikationen filtern

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Zitationsstil: bio1

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33 Publikationen

Alle markieren

[33]
2020 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2944327
Panda A, Yadav A, Yeerna H, Singh A, Biehl M, Lux M, Schulz A, Klecha T, Doniach S, Khiabanian H, Ganesan S, Tamayo P, Bhanot G (2020)
Tissue- and development-stage-specific mRNA and heterogeneous CNV signatures of human ribosomal proteins in normal and cancer samples.
Nucleic acids research.
PUB | DOI | PubMed | Europe PMC
 
[32]
2020 | Konferenzbeitrag | PUB-ID: 2943260
Schulz A, Hinder F, Hammer B (2020)
DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction.
In: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, {IJCAI-20}. .
PUB | DOI | Download (ext.)
 
[31]
2020 | Konferenzbeitrag | Im Druck | PUB-ID: 2941931
Paaßen B, Schulz A (In Press)
Reservoir memory machines.
In: Proceedings of the 28th European Symposium on Artificial Neural Networks (ESANN 2020). Verleysen M (Ed); Bruges.
PUB | Download (ext.) | arXiv
 
[30]
2019 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2934458 OA
Prahm C, Schulz A, Paaßen B, Schoisswohl J, Kaniusas E, Dorffner G, Hammer B, Aszmann O (2019)
Counteracting Electrode Shifts in Upper-Limb Prosthesis Control via Transfer Learning.
IEEE Transactions on Neural Systems and Rehabilitation Engineering 27(5): 956-962.
PUB | PDF | DOI | WoS | PubMed | Europe PMC
 
[29]
2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914505
Paaßen B, Schulz A, Hahne J, Hammer B (2018)
Expectation maximization transfer learning and its application for bionic hand prostheses.
Neurocomputing 298: 122-133.
PUB | DOI | Download (ext.) | WoS | arXiv
 
[28]
2018 | Konferenzbeitrag | PUB-ID: 2930001 OA
Schulz A, Queißer J, Ishihara H, Asada M (2018)
Transfer Learning of Complex Motor Skills on the Humanoid Robot Affetto.
Presented at the International Conference on Development and Learning and on Epigenetic Robotics 2018 (ICDL-EPIROB2018), Tokyo (In Press).
PUB | PDF
 
[27]
2018 | Konferenzbeitrag | PUB-ID: 2916318
Berger K, Schulz A, Paaßen B, Hammer B (2018)
Linear Supervised Transfer Learning for the Large Margin Nearest Neighbor Classifier.
Presented at the SSCI CIDM 2017.
PUB | DOI
 
[26]
2017 | Datenpublikation | PUB-ID: 2912671 OA
Paaßen B, Schulz A (2017)
Linear Supervised Transfer Learning Toolbox.
Bielefeld University.
PUB | Dateien verfügbar | DOI
 
[25]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909369 OA
Paaßen B, Schulz A, Hahne J, Hammer B (2017)
An EM transfer learning algorithm with applications in bionic hand prostheses.
In: Proceedings of the 25th European Symposium on Artificial Neural Networks (ESANN 2017). Verleysen M (Ed); Bruges: i6doc.com: 129-134.
PUB | PDF
 
[24]
2017 | Bielefelder E-Dissertation | PUB-ID: 2914256 OA
Schulz A (2017)
Discriminative dimensionality reduction: variations, applications, interpretations.
Bielefeld: Universität Bielefeld.
PUB | PDF
 
[23]
2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2909372 OA
Schulz A, Brinkrolf J, Hammer B (2017)
Efficient Kernelization of Discriminative Dimensionality Reduction.
Neurocomputing 268(SI): 34-41.
PUB | PDF | DOI | WoS
 
[22]
2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2909037 OA
Prahm C, Schulz A, Paaßen B, Aszmann O, Hammer B, Dorffner G (2017)
Echo State Networks as Novel Approach for Low-Cost Myoelectric Control.
In: Proceedings of the 16th Conference on Artificial Intelligence in Medicine (AIME 2017). ten Telje A, Popow C, Holmes JH, Sacchi L (Eds); Lecture Notes in Computer Science, 10259. Springer: 338--342.
PUB | Dateien verfügbar | DOI
 
[21]
2016 | Konferenzbeitrag | E-Veröff. vor dem Druck | PUB-ID: 2904909 OA
Schulz A, Hammer B (2016)
Discriminative Dimensionality Reduction in Kernel Space.
In: ESANN2016 Proceedings. 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium,27-29 April 2016. i6doc.com.
PUB | PDF
 
[20]
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2905855
Paaßen B, Schulz A, Hammer B (2016)
Linear Supervised Transfer Learning for Generalized Matrix LVQ.
In: Proceedings of the Workshop New Challenges in Neural Computation 2016. Hammer B, Martinetz T, Villmann T (Eds); Machine Learning Reports, 11-18.
PUB | Download (ext.)
 
[19]
2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2904178 OA
Prahm C, Paaßen B, Schulz A, Hammer B, Aszmann O (2016)
Transfer Learning for Rapid Re-calibration of a Myoelectric Prosthesis after Electrode Shift.
In: Converging Clinical and Engineering Research on Neurorehabilitation II: Proceedings of the 3rd International Conference on NeuroRehabilitation (ICNR2016). Ibáñez J, Gonzáles-Vargas J, Azorín JM, Akay M, Pons JL (Eds); Springer: 153--157.
PUB | PDF | DOI | Download (ext.)
 
[18]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2671047 OA
Gisbrecht A, Schulz A, Hammer B (2015)
Parametric nonlinear dimensionality reduction using kernel t-SNE.
Neurocomputing 147: 71-82.
PUB | PDF | DOI | WoS
 
[17]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2903777 OA
Schulz A, Mokbel B, Biehl M, Hammer B (2015)
Inferring Feature Relevances From Metric Learning.
In: 2015 IEEE Symposium Series on Computational Intelligence. Piscataway, NJ: IEEE.
PUB | PDF | DOI
 
[16]
2015 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2766822 OA
Schulz A, Gisbrecht A, Hammer B (2015)
Using Discriminative Dimensionality Reduction to Visualize Classifiers.
Neural Processing Letters 42(1): 27-54.
PUB | PDF | DOI | WoS
 
[15]
2015 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2900303 OA
Schulz A, Hammer B (2015)
Visualization of Regression Models Using Discriminative Dimensionality Reduction.
In: Computer Analysis of Images and Patterns. Lecture Notes in Computer Science, 9257. Cham: Springer Science + Business Media: 437-449.
PUB | PDF | DOI
 
[14]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900325 OA
Blöbaum P, Schulz A, Hammer B (2015)
Unsupervised Dimensionality Reduction for Transfer Learning.
In: Proceedings. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen M (Ed); Louvain-la-Neuve: Ciaco: 507-512.
PUB | PDF
 
[13]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900319
Schulz A, Hammer B (2015)
Discriminative dimensionality reduction for regression problems using the Fisher metric.
In: 2015 International Joint Conference on Neural Networks (IJCNN). Institute of Electrical & Electronics Engineers (IEEE): 1-8.
PUB | DOI
 
[12]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2783369 OA
Mokbel B, Schulz A (2015)
Towards Dimensionality Reduction for Smart Home Sensor Data.
In: Proceedings of the Workshop New Challenges in Neural Computation (NC² 2015). Hammer B, Martinetz T, Villmann T (Eds); Machine Learning Reports, 41-48.
PUB | PDF | Download (ext.)
 
[11]
2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900318
Schulz A, Hammer B (2015)
Metric Learning in Dimensionality Reduction.
In: Proceedings of the International Conference on Pattern Recognition Applications and Methods. Scitepress: 232-239.
PUB | DOI
 
[10]
2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900320
Frenay B, Hofmann D, Schulz A, Biehl M, Hammer B (2014)
Valid interpretation of feature relevance for linear data mappings.
In: 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). Institute of Electrical & Electronics Engineers (IEEE): 149-156.
PUB | DOI
 
[9]
2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2673557
Schulz A, Gisbrecht A, Hammer B (2014)
Relevance learning for dimensionality reduction.
In: ESANN, 22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen M (Ed); Bruges, Belgium: i6doc.com: 165-170.
PUB
 
[8]
2014 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2900322
Bloebaum P, Schulz A (2014)
Transfer Learning without given Correspondences.
In: Proceedings of the Workshop New Challenges in Neural Computation (NC² 2014). Hammer B, Martinetz T, Villmann T (Eds); Machine Learning Reports, 42-51.
PUB
 
[7]
2014 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2900324
Gisbrecht A, Schulz A, Hammer B (2014)
Discriminative Dimensionality Reduction for the Visualization of Classifiers.
In: Pattern Recognition Applications and Methods. Advances in Intelligent Systems and Computing, 318. Cham: Springer Science + Business Media: 39-56.
PUB | DOI
 
[6]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622454
Hammer B, Gisbrecht A, Schulz A (2013)
Applications of discriminative dimensionality reduction.
In: Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods. SCITEPRESS: 33-41.
PUB | DOI
 
[5]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622456
Schulz A, Gisbrecht A, Hammer B (2013)
Using Nonlinear Dimensionality Reduction to Visualize Classifiers.
In: Advances in computational intelligence. Proceedings. Vol 1. Rojas I, Joya G, Gabestany J (Eds); Lecture Notes in Computer Science, 7902. Springer: 59-68.
PUB | DOI | WoS
 
[4]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622466
Vukanovicz S, Schulz A, Haschke R, Ritter H (2013)
Learning the Appropriate Model Population Structures for Locally Weighted Regression.
In: Workshop New Challenges in Neural Computation 2013. Machine Learning Reports, 2013. Bielefeld: Universität Bielefeld: 87.
PUB
 
[3]
2013 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622467
Schulz A, Gisbrecht A, Hammer B (2013)
Classifier inspection based on different discriminative dimensionality reductions.
In: Workshop NC^2 2013. TR Machine Learning Reports: 77-86.
PUB
 
[2]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622449
Schulz A, Gisbrecht A, Bunte K, Hammer B (2012)
How to visualize a classifier?
In: Proceedings of the Workshop - New Challenges in Neural Computation 2012. Machine Learning Reports: 73-83.
PUB
 
[1]
2012 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2622453
Hammer B, Gisbrecht A, Schulz A (2012)
How to Visualize Large Data Sets?
Presented at the Workshop Advances in Self-Organizing Maps (WSOM), Santiago, Chile.
PUB | DOI
 

Suche

Publikationen filtern

Darstellung / Sortierung

Zitationsstil: bio1

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