NIPS Proceedings
^{β}
Books
Matthias Hein
21 Papers
Generalized Matrix Means for Semi-Supervised Learning with Multilayer Graphs
(2019)
Provably robust boosted decision stumps and trees against adversarial attacks
(2019)
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation
(2017)
Clustering Signed Networks with the Geometric Mean of Laplacians
(2016)
Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods
(2016)
Efficient Output Kernel Learning for Multiple Tasks
(2015)
Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices
(2015)
Top-k Multiclass SVM
(2015)
Tight Continuous Relaxation of the Balanced k-Cut Problem
(2014)
Matrix factorization with binary components
(2013)
The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited
(2013)
Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts
(2011)
Sparse recovery by thresholded non-negative least squares
(2011)
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
(2010)
Getting lost in space: Large sample analysis of the resistance distance
(2010)
Robust Nonparametric Regression with Metric-Space Valued Output
(2009)
Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction
(2009)
Influence of graph construction on graph-based clustering measures
(2008)
Non-parametric Regression Between Manifolds
(2008)
Manifold Denoising
(2006)
Measure Based Regularization
(2003)