Suchergebnisse

Zeitschriftenartikel (5)

  1. 1.
    Zeitschriftenartikel
    Maier, M.; von Luxburg, U.; Hein, M.: How the result of graph clustering methods depends on the construction of the graph. ESAIM: Probability and Statistics 17, S. 370 - 418 (2013)
  2. 2.
    Zeitschriftenartikel
    Steinke, F.; Hein, M.; Schölkopf, B.: Nonparametric Regression between General Riemannian Manifolds. SIAM Journal on Imaging Sciences 3 (3), S. 527 - 563 (2010)
  3. 3.
    Zeitschriftenartikel
    Steinke, F.; Hein, M.; Peters, J.; Schölkopf, B.: Manifold-valued Thin-plate Splines with Applications in Computer Graphics. Computer Graphics Forum 27 (2), S. 437 - 448 (2008)
  4. 4.
    Zeitschriftenartikel
    Hein, M.; Audibert, J.-Y.; von Luxburg, U.: Graph Laplacians and their Convergence on Random Neighborhood Graphs. The Journal of Machine Learning Research 8, S. 1325 - 1370 (2007)
  5. 5.
    Zeitschriftenartikel
    Hein, M.; Bousquet, O.; Schölkopf, B.: Maximal Margin Classification for Metric Spaces. Journal of Computer and System Sciences 71 (3), S. 333 - 359 (2005)

Konferenzbeitrag (13)

  1. 6.
    Konferenzbeitrag
    von Luxburg, U.; Radl, A.; Hein, M.: Getting lost in space: Large sample analysis of the resistance distance. Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Vancouver, BC, Canada, 06. Dezember 2010 - 11. Dezember 2010. Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, S. 2622 - 2630 (2011)
  2. 7.
    Konferenzbeitrag
    Maier, M.; von Luxburg, U.; Hein, M.: Influence of graph construction on graph-based clustering measures. In: Advances in neural information processing systems 21, S. 1025 - 1032 (Hg. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, 08. Dezember 2008 - 10. Dezember 2008. Curran, Red Hook, NY, USA (2009)
  3. 8.
    Konferenzbeitrag
    Steinke, F.; Hein, M.: Non-parametric Regression between Riemannian Manifolds. In: Advances in neural information processing systems 21, S. 1561 - 1568 (Hg. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, 08. Dezember 2008 - 10. Dezember 2008. Curran, Red Hook, NY, USA (2009)
  4. 9.
    Konferenzbeitrag
    Maier, M.; Hein, M.; von Luxburg, U.: Cluster Identification in Nearest-Neighbor Graphs. In: Algorithmic Learning Theory: 18th International Conference, ALT 2007, Sendai, Japan, October 1-4, 2007, S. 196 - 210 (Hg. Hutter, M.; Servedio, R.; Takimoto, E.). 18th International Conference on Algorithmic Learning Theory (ALT 2007), Sendai, Japan, 01. Oktober 2007 - 04. Oktober 2007. Springer, Berlin, Germany (2007)
  5. 10.
    Konferenzbeitrag
    Hein, M.; Maier, M.: Manifold Denoising. In: Advances in Neural Information Processing Systems 19, S. 561 - 568 (Hg. Schölkopf, B.; Platt, J.; Hoffman, T.). Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), Vancouver, BC, Canada, 04. Dezember 2006 - 07. Dezember 2006. MIT Press, Cambridge, MA, USA (2007)
  6. 11.
    Konferenzbeitrag
    Hein, M.; Maier, M.: Manifold Denoising as Preprocessing for Finding Natural Representations of Data. In: Twenty-Second AAAI Conference on Artificial Intelligence (AAAI-07), S. 1646 - 1649. Twenty-Second AAAI Conference on Artificial Intelligence (AAAI-07), Vancouver, BC, Canada, 22. Juli 2007 - 26. Juli 2007. AAAI Press, Menlo Park, CA, USA (2007)
  7. 12.
    Konferenzbeitrag
    Hein, M.: Uniform Convergence of Adaptive Graph-Based Regularization. In: Learning Theory: 19th Annual Conference on Learning Theory, COLT 2006, Pittsburgh, PA, USA, June 22-25, 2006, S. 50 - 64 (Hg. Lugosi, G.; Simon, H.). 19th Annual Conference on Learning Theory (COLT 2006), Pittsburgh, PA, USA, 22. Juni 2006 - 25. Juni 2006. Springer, Berlin, Germany (2006)
  8. 13.
    Konferenzbeitrag
    Hein, M.; Audibert, J.-Y.: Intrinsic Dimensionality Estimation of Submanifolds in Rd. In: ICML '05: 22nd international conference on Machine learning, S. 289 - 296 (Hg. Dzeroski, S.; de Raedt, L.; Wrobel, S.). 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, 07. August 2005 - 11. August 2005. ACM Press, New York, NY, USA (2005)
  9. 14.
    Konferenzbeitrag
    Hein, M.; Audibert, J.; von Luxburg, U.: From Graphs to Manifolds: Weak and Strong Pointwise Consistency of Graph Laplacians. In: Learning Theory: 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005, S. 470 - 485 (Hg. Auer, P.; Meir, R.). 18th Annual Conference on Learning Theory (COLT 2005), Bertinoro, Italy, 27. Juni 2005 - 30. Juni 2005. Springer, Berlin, Germany (2005)
  10. 15.
    Konferenzbeitrag
    Hein, M.; Bousquet, O.: Hilbertian Metrics and Positive Definite Kernels on Probability Measures. In: AISTATS 2005: Tenth International Workshop onArtificial Intelligence and Statistics, S. 136 - 143 (Hg. Cowell, R.; Ghahramani, Z.). Tenth International Workshop on Artificial Intelligence and Statistics (AI Statistics 2005), Barbados, 06. Januar 2005 - 08. Januar 2005. The Society for Artificial Intelligence and Statistics (2005)
  11. 16.
    Konferenzbeitrag
    Hein, H.; Lal, T.; Bousquet, O.: Hilbertian Metrics on Probability Measures and their Application in SVM's. In: Pattern Recognition: 26th DAGM Symposium, Tübingen, Germany, August 30 - September 1, 2004, S. 270 - 277 (Hg. Rasmussen, C.; Bülthoff, H.; Schölkopf, B.; Giese, M.). 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Tübingen, Germany, 30. August 2004 - 01. September 2004. Springer, Berlin, Germany (2004)
  12. 17.
    Konferenzbeitrag
    Bousquet, O.; Chapelle, O.; Hein, M.: Measure Based Regularization. In: Advances in Neural Information Processing Systems 16, S. 1221 - 1228 (Hg. Thrun, S.; Saul, L.; Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, 09. Dezember 2003 - 11. Dezember 2003. MIT Press, Cambridge, MA, USA (2004)
  13. 18.
    Konferenzbeitrag
    Hein, M.; Bousquet, O.: Maximal Margin Classification for Metric Spaces. In: Learning Theory and Kernel Machines: 16th Annual Conference on Learning Theory and 7th Kernel Workshop, COLT/Kernel 2003, Washington, DC, USA, August 24-27, 2003, S. 72 - 86 (Hg. Schölkopf, B.; Warmuth, M.). 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), Washington, DC, USA, 24. August 2003 - 27. August 2003. Springer, Berlin, Germany (2004)

Vortrag (1)

  1. 19.
    Vortrag
    Steinke, F.; Hein, M.; Schölkopf, B.: Thin-Plate Splines Between Riemannian Manifolds. HIM Workshop: Geometry and Statistics of Shapes 2008, Bonn, Germany (2008)

Hochschulschrift - Doktorarbeit (1)

  1. 20.
    Hochschulschrift - Doktorarbeit
    Hein, M.: Geometrical aspects of statistical learning theory. Dissertation, 153 S., Technische Universität Darmstadt, Darmstadt, Germany (2005)
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