| Clustering signed networks with the geometric mean of Laplacians P Mercado, F Tudisco, M Hein NeurIPS 2016, 4421-4429, 2016 | 29 | 2016 |
| The power mean Laplacian for multilayer graph clustering P Mercado, A Gautier, F Tudisco, M Hein AISTATS 2018, 2018 | 16 | 2018 |
| Community detection in networks via nonlinear modularity eigenvectors F Tudisco, P Mercado, M Hein SIAM Journal on Applied Mathematics 78 (5), 2393-2419, 2018 | 11 | 2018 |
| Spectral Clustering of Signed Graphs via Matrix Power Means P Mercado, F Tudisco, M Hein ICML 2019, 2019 | 10 | 2019 |
| Node classification for signed networks using diffuse interface methods P Mercado, J Bosch, M Stoll ECMLPKDD 2019, 2019 | 9* | 2019 |
| Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs P Mercado, F Tudisco, M Hein NeurIPS 2019, 2019 | 7 | 2019 |
| Towards Lyrics Spotting in the SyncGlobal Project C Dittmar, P Mercado, H Grossmann, E Cano 3rd International Workshop on Cognitive Information Processing (CIP), 2012 | 7 | 2012 |
| Feature selection in clustering with constraints: Application to active exploration of music collections P Mercado, H Lukashevich ICMLA 2010, 649-654, 2010 | 3 | 2010 |
| Applying constrained clustering for active exploration of music collections P Mercado, H Lukashevich 1st Workshop on Music Recommendation and Discovery (WOMRAD), 39, 2010 | 2 | 2010 |
| Graph-based PDEs: Laplacians, eigeninformation, and semi-supervised learning J Bosch, S Klamt, P Mercado, M Stoll XXI Householder Symposium on Numerical Linear Algebra, 84, 2020 | | 2020 |
Matthias HeinProfessor of Computer Science, University of TübingenVerified email at uni-tuebingen.de
