A tutorial on spectral clustering U Von Luxburg Statistics and computing 17 (4), 395-416, 2007 | 10311 | 2007 |
Consistency of spectral clustering U Von Luxburg, M Belkin, O Bousquet The Annals of Statistics, 555-586, 2008 | 641 | 2008 |
From graphs to manifolds–weak and strong pointwise consistency of graph Laplacians M Hein, JY Audibert, U Luxburg International Conference on Computational Learning Theory, 470-485, 2005 | 353 | 2005 |
Clustering stability: an overview U Von Luxburg Now Publishers Inc, 2010 | 297 | 2010 |
Graph laplacians and their convergence on random neighborhood graphs. M Hein, JY Audibert, U Luxburg Journal of Machine Learning Research 8 (6), 2007 | 285 | 2007 |
A sober look at clustering stability S Ben-David, U Luxburg, D Pál International conference on computational learning theory, 5-19, 2006 | 272 | 2006 |
Clustering: Science or art? U Von Luxburg, RC Williamson, I Guyon Proceedings of ICML workshop on unsupervised and transfer learning, 65-79, 2012 | 221 | 2012 |
Influence of graph construction on graph-based clustering measures M Maier, U Luxburg, M Hein Advances in neural information processing systems 21, 2008 | 203 | 2008 |
Statistical learning theory: Models, concepts, and results U Von Luxburg, B Schölkopf Handbook of the History of Logic 10, 651-706, 2011 | 196 | 2011 |
Curran Associates I Guyon, UV Luxburg, S Bengio, H Wallach, R Fergus, S Vishwanathan, ... Inc.: Red Hook, NY, USA 30, 2017 | 195 | 2017 |
Distance-Based Classification with Lipschitz Functions. U von Luxburg, O Bousquet J. Mach. Learn. Res. 5 (Jun), 669-695, 2004 | 175 | 2004 |
Getting lost in space: Large sample analysis of the resistance distance U Luxburg, A Radl, M Hein Advances in neural information processing systems 23, 2010 | 152 | 2010 |
Limits of spectral clustering U Luxburg, O Bousquet, M Belkin Advances in neural information processing systems 17, 2004 | 148 | 2004 |
Clustering: Science or art I Guyon, U Von Luxburg, RC Williamson NIPS 2009 workshop on clustering theory, 1-11, 2009 | 146 | 2009 |
Optimal construction of k-nearest-neighbor graphs for identifying noisy clusters M Maier, M Hein, U Von Luxburg Theoretical Computer Science 410 (19), 1749-1764, 2009 | 136 | 2009 |
Hitting and commute times in large random neighborhood graphs U Von Luxburg, A Radl, M Hein The Journal of Machine Learning Research 15 (1), 1751-1798, 2014 | 122 | 2014 |
Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures O Bousquet, U von Luxburg, G Rätsch Springer, 2011 | 121 | 2011 |
Towards a statistical theory of clustering U Von Luxburg, S Ben-David Pascal workshop on statistics and optimization of clustering, 20-26, 2005 | 111 | 2005 |
Curran Associates DD Lee, M Sugiyama, UV Luxburg, I Guyon, R Garnett Inc.: Red Hook, NY, USA 29, 2016 | 87 | 2016 |
Nearest neighbor clustering: A baseline method for consistent clustering with arbitrary objective functions S Bubeck, U Luxburg The Journal of Machine Learning Research 10, 657-698, 2009 | 76 | 2009 |