Articles (5): |
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Steinke F , Hein M and Schölkopf B (September-2010) Nonparametric Regression between General Riemannian Manifolds
SIAM Journal on Imaging Sciences 3(3) 527-563.

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Steinke F , Hein M , Peters J and Schölkopf B (April-2008) Manifold-valued Thin-plate Splines
with Applications in Computer Graphics
Computer Graphics Forum 27(2) 437-448.
  
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Hein M , Audibert J-Y and von Luxburg U (June-2007) Graph Laplacians and their Convergence on Random Neighborhood Graphs
Journal of Machine Learning Research 8 1325-1370.

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Hein M , Bousquet O and Schölkopf B (October-2005) Maximal Margin Classification for Metric Spaces
Journal of Computer and System Sciences 71(3) 333-359.
 
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Frauendiener J and Hein M (2002) Numerical evolution of axisymmetric, isolated
systems in general relativity
Physical Review D 66 124004-124004.
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Conference papers (11): |
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von Luxburg U , Radl A and Hein M (June-2011) Getting lost in space: Large sample analysis of the resistance distance
In: Advances in Neural Information Processing Systems 23, Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010), Curran, Red Hook, NY, USA, 2622-2630.

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Maier M , von Luxburg U and Hein M (June-2009) Influence of graph construction on graph-based clustering measures
In: Advances in neural information processing systems 21, Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), Curran, Red Hook, NY, USA, 1025-1032.

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Hein M and Maier M (September-2007) Manifold Denoising
In: Advances in Neural Information Processing Systems 19, Twentieth Annual Conference on Neural Information Processing Systems (NIPS 2006), MIT Press, Cambridge, MA, USA, 561-568.

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Hein M and Maier M (July-2007) Manifold Denoising as Preprocessing for Finding Natural Representations of Data
In: AAAI-07, Twenty-Second AAAI Conference on Artificial Intelligence (AAAI-07), AAAI Press, Menlo Park, CA, USA, 1646-1649.

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Hein M (September-2006) Uniform Convergence of Adaptive Graph-Based Regularization
In: COLT 2006, 19th Annual Conference on Learning Theory, Springer, Berlin, Germany, 50-64.
 
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Hein M and Bousquet O (January-2005) Hilbertian Metrics and Positive Definite Kernels on Probability Measures
In: AISTATS 2005, Tenth International Workshop on Artificial Intelligence and Statistics (AI & Statistics 2005), 136-143.

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Hein M , Audibert J and von Luxburg U (2005) From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians
Conference on Learning Theory, 470-485.
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Hein M and Audibert Y (2005) Intrinsic Dimensionality Estimation of Submanifolds in Euclidean space
ICML Bonn, 289.
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Bousquet O , Chapelle O and Hein M (June-2004) Measure Based Regularization
In: Advances in Neural Information Processing Systems 16, Seventeenth Annual Conference on Neural Information Processing Systems (NIPS 2003), MIT Press, Cambridge, MA, USA, 1221-1228.

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Hein M and Bousquet O (February-2004) Maximal Margin Classification for Metric Spaces
16. Annual Conference on Computational Learning Theory / COLT Kernel 2003, Springer Verlag, Heidelberg, Germany, 72-86.
  
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Hein H , Lal TN and Bousquet O (2004) Hilbertian Metrics on Probability Measures and their Application in SVM's
Pattern Recognition, Proceedings of th 26th DAGM Symposium, 3175, 270-277.

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Technical reports (3): |
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Hein M , Steinke F and Schölkopf B : Energy Functionals for
Manifold-valued Mappings and
Their Properties, 167, Max Planck Institute for Biological Cybernetics, Tübingen, (January-2008).
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Hein M and Bousquet O : Hilbertian Metrics and Positive Definite Kernels on Probability Measures, 126, (July-2004).
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Hein M and Bousquet O : Kernels, Associated Structures and Generalizations, 127, (July-2004).
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Theses (1): |
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Hein M : Geometrical aspects of statistical learning theory, Darmstadt, Darmstadt, (November-2005).
PhD thesis
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Talks (1): |
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Steinke F , Hein M and Schölkopf B (June-2008): Thin-Plate Splines Between Riemannian Manifolds, Workshop on Geometry and Statistics of Shapes 2008, Bonn, Germany.
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