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ORCID12. WSOM 2017: Nancy, France
- Jean-Charles Lamirel, Marie Cottrell, Madalina Olteanu:
12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017, Nancy, France, June 28-30, 2017. IEEE 2017, ISBN 978-1-5090-6638-4
Session 1: Theoretical Aspects 1
- Nicolas P. Rougier
, Yann Boniface:
Motivated self-organization. 9-12 - César Torres-Huitzil, Oleksandr V. Popovych, Bernard Girau:
Fault tolerance of self organizing maps. 13-20 - Ryad A. Zemouri:
An evolutionary building algorithm for Deep Neural Networks. 21-27 - Michael Kirby, Chris Peterson:
Visualizing data sets on the Grassmannian using self-organizing mappings. 28-33 - Erzsébet Merényi, Joshua Taylor:
SOM-empowered graph segmentation for fast automatic clustering of large and complex data. 34-42
Session 2: Poster Session
- Paulo Afonso Mei, Cleyton de Carvalho Carneiro, Michelle Chaves Kuroda, Stephen J. Fraser, Li Li Min, Fabiano Reis:
Self-organizing maps as a tool for segmentation of Magnetic Resonance Imaging (MRI) of relapsing-remitting multiple sclerosis. 43-49 - Pitoyo Hartono, Yuto Take:
Pairwise elastic self-organizing maps. 50-56 - Joel I. Deichmann, Abdolreza Eshghi, Dominique Haughton, Mingfei Li:
Using SOMbrero to examine the economic convergence of European countries from 2001-2013. 57-62 - Cleyton de Carvalho Carneiro, Dayana Niazabeth Del Valle Silva Yanez, Carina Ulsen, Stephen J. Fraser, Juliana Livi Antoniassi, Simone P. A. Paz, Romulo Simoes Angelica, Henrique Kahn:
Imputation of reactive silica and available alumina in bauxites by self-organizing maps. 63-68 - Thomas Villmann, Michael Biehl, Andrea Villmann, Sascha Saralajew:
Fusion of deep learning architectures, multilayer feedforward networks and learning vector quantizers for deep classification learning. 69-76 - Alfred Ultsch, Michael C. Thrun:
Credible visualizations for planar projections. 77-81
Session 3: Image and Signal
- Nobuo Matsuda, Heizo Tokutaka, Hideaki Sato, Fumiaki Tajima, Reiji Kawata:
Applying the significance degree by SOM to image analysis of fundus using the filter bank. 82-87 - Patrick O'Driscoll, Erzsébet Merényi, Robert G. Grossman:
Using spatial characteristics to aid automation of SOM segmentation of functional image data. 98-95 - Cynthia Faure, Madalina Olteanu, Jean-Marc Bardet, Jérôme Lacaille:
Using self-organizing maps for clustering anc labelling aircraft engine data phases. 96-103
Invited talk
- Nathalie Villa-Vialaneix:
Stochastic self-organizing map variants with the R package SOMbrero. 104-110
Session 4: Applications to Real World Problems
- Barbara Pisano, Alessandra Fanni, César Alexandre Teixeira, António Dourado:
Application of self organizing map to identify nocturnal epileptic seizures. 111-117 - David N. Coelho, Guilherme A. Barreto, Cláudio M. S. Medeiros:
Detection of short circuit faults in 3-phase converter-fed induction motors using kernel SOMs. 118-124 - Jan Faigl:
Self-organizing map for orienteering problem with dubins vehicle. 125-132
Session 5: Theoretical Aspects 2
- Alexander Gepperth:
An energy-based SOM model not requiring periodic boundary conditions. 133-138 - Michiel Straat, Marika Kaden, Matthias Gay, Thomas Villmann, Alexander Lampe, Udo Seiffert, Michael Biehl, Friedrich Melchert:
Prototypes and matrix relevance learning in complex fourier space. 139-144 - Gabriele Bani, Udo Seiffert, Michael Biehl, Friedrich Melchert:
Adaptive basis functions for prototype-based classification of functional data. 145-152 - Alexander Gepperth, Cem Karaoguz:
Incremental learning with self-organizing maps. 153-160 - Ludovic Platon, Farida Zehraoui, Fariza Tahi:
Self-organizing maps with supervised layer. 161-168
Session 6: Applications in Social Sciences
- Dounia Mulders, Cyril de Bodt, Johannes Bjelland, Alex 'Sandy' Pentland, Michel Verleysen, Yves-Alexandre de Montjoye:
Improving individual predictions using social networks assortativity. 169-176 - Marie Cottrell, Madalina Olteanu, Julien Randon-Furling, Aurélien Hazan:
Multidimensional urban segregation: An exploratory case study. 177-183 - César Lincoln C. Mattos, Guilherme A. Barreto, Dennis Horstkemper, Bernd Hellingrath:
Metaheuristic optimization for automatic clustering of customer-oriented supply chain data. 184-191
Session 7: LVQ
- Frank-Michael Schleif:
Small sets of random Fourier features by kernelized Matrix LVQ. 192-196 - Michael LeKander, Michael Biehl, Harm de Vries:
Empirical evaluation of gradient methods for matrix learning vector quantization. 197-204 - Johannes Brinkrolf, Barbara Hammer:
Probabilistic extension and reject options for pairwise LVQ. 205-212 - David Nova, Pablo A. Estévez:
Spectral regularization in generalized matrix learning vector quantization. 213-219
Session 8: Relational Networks and Neural Gas
- Marika Kaden, David Nebel, Friedrich Melchert, Andreas Backhaus, Udo Seiffert, Thomas Villmann:
Data dependent evaluation of dissimilarities in nearest prototype vector quantizers regarding their discriminating abilities. 220-226 - Iván Machón González, Hilario López García:
Nonlinear dynamic identification using supervised neural gas algorithm. 227-233 - Tina Geweniger, Thomas Villmann:
Relational and median variants of Possibilistic Fuzzy C-Means. 234-240 - Jorge R. Vergara, Pablo A. Estévez:
A strategy for time series prediction using Segment Growing Neural Gas. 241-248
Invited talk
- Yann Guermeur:
Rademacher complexity of margin multi-category classifiers. 249-254
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