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(2017) An Efficient Multilinear Optimization Framework for Hypergraph Matching.
(2017) Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation.
(2017) The Loss Surface of Deep and Wide Neural Networks.
(2017) Simple Does It: Weakly Supervised Instance and Semantic Segmentation.
(2017) Variants of RMSProp and Adagrad with Logarithmic Regret Bounds.
(2016) Loss Functions for Top-k Error: Analysis and Insights.
(2016) Clustering Signed Networks with the Geometric Mean of Laplacians.
(2016) Globally Optimal Training of Generalized Polynomial Neural Networks with Nonlinear Spectral Methods.
(2016) Improved Image Boundaries for Better Video Segmentation.
(2016) Latent Embeddings for Zero-Shot Classification.
(2016) Weakly Supervised Object Boundaries.
(2015) Classifier based graph construction for video segmentation.
(2015) Efficient Output Kernel Learning for Multiple Tasks.
(2015) Correction of noisy labels via mutual consistency check.
(2015) Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 15361).
(2015) Regularization-Free Estimation in Trace Regression with Symmetric Positive Semidefinite Matrices.
(2015) Top-k Multiclass SVM.
(2015) A flexible tensor block coordinate ascent scheme for hypergraph matching.
(2014) Learning using privileged information: SV M+ and weighted SVM.
(2014) Scalable Multitask Representation Learning for Scene Classification.
(2014) Hitting and commute times in large random neighborhood graphs.
(2014) Learning Must-Link Constraints for Video Segmentation Based on Spectral Clustering.
(2014) Robust PCA: Optimization of the Robust Reconstruction Error Over the Stiefel Manifold.
(2014) Tight Continuous Relaxation of the Balanced k-Cut Problem.
(2013) Constrained fractional set programs and their application in local clustering and community detection.
(2013) Towards realistic team formation in social networks based on densest subgraphs.
(2013) Matrix factorization with binary components.
(2013) The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited.
(2013) Towards realistic team formation in social networks based on densest subgraphs.
(2012) Constrained 1-Spectral Clustering.
(2012) Isotope pattern deconvolution for peptide mass spectrometry by non-negative least squares/least absolute deviation template matching.
(2011) Beyond Spectral Clustering - Tight Relaxations of Balanced Graph Cuts.
(2011) Mathematical and Computational Foundations of Learning Theory (Dagstuhl Seminar 11291).
(2011) Sparse recovery by thresholded non-negative least squares.
(2010) Getting lost in space: Large sample analysis of the resistance distance.
(2010) An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA.
(2010) Nonparametric Regression between General Riemannian Manifolds.
(2009) Large-scale antibody profiling of human blood sera: The future of molecular diagnosis.
(2009) Optimal construction of k-nearest-neighbor graphs for identifying noisy clusters.
(2009) Robust Nonparametric Regression with Metric-Space Valued Output.
(2009) Semi-supervised Regression using Hessian energy with an application to semi-supervised dimensionality reduction.
(2009) Spectral clustering based on the graph \emphp-Laplacian.
(2008) Enhancement of Bright Video Features for HDR Displays.
(2008) Influence of graph construction on graph-based clustering measures.
(2008) Manifold-valued Thin-Plate Splines with Applications in Computer Graphics.
(2008) Non-parametric Regression Between Manifolds.
(2007) Cluster Identification in Nearest-Neighbor Graphs.
(2007) Graph Laplacians and their Convergence on Random Neighborhood Graphs.
(2007) Manifold Denoising as Preprocessing for Finding Natural Representations of Data.
(2006) Manifold Denoising.
(2006) Uniform Convergence of Adaptive Graph-Based Regularization.
(2005) From Graphs to Manifolds - Weak and Strong Pointwise Consistency of Graph Laplacians.
(2005) Geometrical aspects of statistical learning theory.
(2005) Hilbertian Metrics and Positive Definite Kernels on Probability Measures.
(2005) Intrinsic dimensionality estimation of submanifolds in Rd.
(2005) Maximal margin classification for metric spaces.
(2004) Hilbertian Metrics on Probability Measures and Their Application in SVM?s.
(2003) Maximal Margin Classification for Metric Spaces.
(2003) Measure Based Regularization.