Matthias Hein
Matthias Hein
Professor of Computer Science, University of Tübingen
Verified email at uni-tuebingen.de - Homepage
Title
Cited by
Cited by
Year
Latent embeddings for zero-shot classification
Y Xian, Z Akata, G Sharma, Q Nguyen, M Hein, B Schiele
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016
3972016
From graphs to manifolds–weak and strong pointwise consistency of graph Laplacians
M Hein, JY Audibert, U Von Luxburg
International Conference on Computational Learning Theory, 470-485, 2005
3162005
Simple does it: Weakly supervised instance and semantic segmentation
A Khoreva, R Benenson, J Hosang, M Hein, B Schiele
Proceedings of the IEEE conference on computer vision and pattern …, 2017
2842017
Spectral clustering based on the graph p-Laplacian
T Bühler, M Hein
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
2682009
Graph Laplacians and their convergence on random neighborhood graphs
M Hein, JY Audibert, U Luxburg
Journal of Machine Learning Research 8 (Jun), 1325-1368, 2007
2582007
Formal guarantees on the robustness of a classifier against adversarial manipulation
M Hein, M Andriushchenko
Advances in Neural Information Processing Systems, 2266-2276, 2017
2372017
Intrinsic dimensionality estimation of submanifolds in Rd
M Hein, JY Audibert
Proceedings of the 22nd international conference on Machine learning, 289-296, 2005
2092005
Manifold denoising
M Hein, M Maier
Advances in neural information processing systems 19, 561-568, 2006
2052006
Hilbertian metrics and positive definite kernels on probability measures
M Hein, O Bousquet
Max Planck Institute for Biological Cybernetics, 2004
1962004
Influence of graph construction on graph-based clustering measures
M Maier, UV Luxburg, M Hein
Advances in neural information processing systems, 1025-1032, 2009
1812009
An inverse power method for nonlinear eigenproblems with applications in 1-spectral clustering and sparse PCA
M Hein, T Bühler
Advances in Neural Information Processing Systems, 847-855, 2010
1772010
The loss surface of deep and wide neural networks
Q Nguyen, M Hein
arXiv preprint arXiv:1704.08045, 2017
1712017
Non-negative least squares for high-dimensional linear models: Consistency and sparse recovery without regularization
M Slawski, M Hein
Electronic Journal of Statistics 7, 3004-3056, 2013
1422013
Measure based regularization
O Bousquet, O Chapelle, M Hein
Advances in Neural Information Processing Systems, 1221-1228, 2004
1392004
Getting lost in space: Large sample analysis of the resistance distance
UV Luxburg, A Radl, M Hein
Advances in Neural Information Processing Systems, 2622-2630, 2010
1322010
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
1252009
Variants of rmsprop and adagrad with logarithmic regret bounds
MC Mukkamala, M Hein
arXiv preprint arXiv:1706.05507, 2017
1162017
Semi-supervised regression using Hessian energy with an application to semi-supervised dimensionality reduction
K Kim, F Steinke, M Hein
Advances in neural information processing systems 22, 979-987, 2009
1032009
Learning using privileged information: SVM+ and weighted SVM
M Lapin, M Hein, B Schiele
Neural Networks 53, 95-108, 2014
1022014
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
962014
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