598 citations · 2.9k across the 89 of their papers we have counts for
7 papers · 2 filters
Loss Functions for Top-k Error: Analysis and Insights
Maksim Lapin, Matthias Hein, Bernt Schiele
In order to push the performance on realistic computer vision tasks, the number of classes in modern benchmark datasets has significantly increased in recent years. This increase i…
Top-k Multiclass SVM
Maksim Lapin, Matthias Hein, Bernt Schiele
Class ambiguity is typical in image classification problems with a large number of classes. When classes are difficult to discriminate, it makes sense to allow k guesses and evalua…
Efficient Output Kernel Learning for Multiple Tasks
Pratik Jawanpuria, Maksim Lapin, Matthias Hein +1
The paradigm of multi-task learning is that one can achieve better generalization by learning tasks jointly and thus exploiting the similarity between the tasks rather than learnin…
Robust PCA: Optimization of the Robust Reconstruction Error over the Stiefel Manifold
Anastasia Podosinnikova, Simon Setzer, Matthias Hein
It is well known that Principal Component Analysis (PCA) is strongly affected by outliers and a lot of effort has been put into robustification of PCA. In this paper we present a n…
Constrained 1-Spectral Clustering
Syama Sundar Rangapuram, Matthias Hein
An important form of prior information in clustering comes in form of cannot-link and must-link constraints. We present a generalization of the popular spectral clustering techniqu…
Tight Continuous Relaxation of the Balanced -Cut Problem
Syama Sundar Rangapuram, Pramod Kaushik Mudrakarta, Matthias Hein
Spectral Clustering as a relaxation of the normalized/ratio cut has become one of the standard graph-based clustering methods. Existing methods for the computation of multiple clus…