Publications of M Hein

Journal Article (5)

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

Conference Paper (14)

6.
Conference Paper
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, December 06, 2010 - December 11, 2010. Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, pp. 2622 - 2630 (2011)
7.
Conference Paper
Kim, K.; Steinke, F.; Hein, M.: Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction. In: Advances in Neural Information Processing Systems 22, pp. 979 - 987 (Eds. Bengio, Y.; Schuurmans, D.; Lafferty, J.; Williams, C.; Culotta, A.). 23rd Annual Conference on Neural Information Processing Systems (NIPS 2009), Vancouver, BC, Canada, December 07, 2009 - December 10, 2009. Curran, Red Hook, NY, USA (2010)
8.
Conference Paper
Maier, M.; von Luxburg, U.; Hein, M.: Influence of graph construction on graph-based clustering measures. In: Advances in neural information processing systems 21, pp. 1025 - 1032 (Eds. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, December 08, 2008 - December 10, 2008. Curran, Red Hook, NY, USA (2009)
9.
Conference Paper
Steinke, F.; Hein, M.: Non-parametric Regression between Riemannian Manifolds. In: Advances in neural information processing systems 21, pp. 1561 - 1568 (Eds. Koller, D.; Schuurmans, D.; Bengio, Y.; Bottou, L.). Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Vancouver, BC, Canada, December 08, 2008 - December 10, 2008. Curran, Red Hook, NY, USA (2009)
10.
Conference Paper
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, pp. 196 - 210 (Eds. Hutter, M.; Servedio, R.; Takimoto, E.). 18th International Conference on Algorithmic Learning Theory (ALT 2007), Sendai, Japan, October 01, 2007 - October 04, 2007. Springer, Berlin, Germany (2007)
11.
Conference Paper
Hein, M.; Maier, M.: Manifold Denoising. In: Advances in Neural Information Processing Systems 19, pp. 561 - 568 (Eds. Schölkopf, B.; Platt, J.; Hoffman, T.). Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), Vancouver, BC, Canada, December 04, 2006 - December 07, 2006. MIT Press, Cambridge, MA, USA (2007)
12.
Conference Paper
Hein, M.; Maier, M.: Manifold Denoising as Preprocessing for Finding Natural Representations of Data. In: Twenty-Second AAAI Conference on Artificial Intelligence (AAAI-07), pp. 1646 - 1649. Twenty-Second AAAI Conference on Artificial Intelligence (AAAI-07), Vancouver, BC, Canada, July 22, 2007 - July 26, 2007. AAAI Press, Menlo Park, CA, USA (2007)
13.
Conference Paper
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, pp. 50 - 64 (Eds. Lugosi, G.; Simon, H.). 19th Annual Conference on Learning Theory (COLT 2006), Pittsburgh, PA, USA, June 22, 2006 - June 25, 2006. Springer, Berlin, Germany (2006)
14.
Conference Paper
Hein, M.; Audibert, J.-Y.: Intrinsic Dimensionality Estimation of Submanifolds in Rd. In: ICML '05: 22nd international conference on Machine learning, pp. 289 - 296 (Eds. Dzeroski, S.; de Raedt, L.; Wrobel, S.). 22nd International Conference on Machine Learning (ICML 2005), Bonn, Germany, August 07, 2005 - August 11, 2005. ACM Press, New York, NY, USA (2005)
15.
Conference Paper
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, pp. 470 - 485 (Eds. Auer, P.; Meir, R.). 18th Annual Conference on Learning Theory (COLT 2005), Bertinoro, Italy, June 27, 2005 - June 30, 2005. Springer, Berlin, Germany (2005)
16.
Conference Paper
Hein, M.; Bousquet, O.: Hilbertian Metrics and Positive Definite Kernels on Probability Measures. In: AISTATS 2005: Tenth International Workshop onArtificial Intelligence and Statistics, pp. 136 - 143 (Eds. Cowell, R.; Ghahramani, Z.). Tenth International Workshop on Artificial Intelligence and Statistics (AI Statistics 2005), Barbados, January 06, 2005 - January 08, 2005. The Society for Artificial Intelligence and Statistics (2005)
17.
Conference Paper
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, pp. 270 - 277 (Eds. Rasmussen, C.; Bülthoff, H.; Schölkopf, B.; Giese, M.). 26th Annual Symposium of the German Association for Pattern Recognition (DAGM 2004), Tübingen, Germany, August 30, 2004 - September 01, 2004. Springer, Berlin, Germany (2004)
18.
Conference Paper
Bousquet, O.; Chapelle, O.; Hein, M.: Measure Based Regularization. In: Advances in Neural Information Processing Systems 16, pp. 1221 - 1228 (Eds. Thrun, S.; Saul, L.; Schölkopf, B.). Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), Vancouver, BC, Canada, December 09, 2003 - December 11, 2003. MIT Press, Cambridge, MA, USA (2004)
19.
Conference Paper
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, pp. 72 - 86 (Eds. Schölkopf, B.; Warmuth, M.). 16th Annual Conference on Learning Theory and 7th Kernel Workshop (COLT/Kernel 2003), Washington, DC, USA, August 24, 2003 - August 27, 2003. Springer, Berlin, Germany (2004)

Talk (1)

20.
Talk
Steinke, F.; Hein, M.; Schölkopf, B.: Thin-Plate Splines Between Riemannian Manifolds. HIM Workshop: Geometry and Statistics of Shapes 2008, Bonn, Germany (2008)
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