7 citations · 7 across the 2 of their papers we have counts for
3 papers
Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring
Sibylle Hess, Wouter Duivesteijn, Decebal Mocanu
We formally prove the connection between k-means clustering and the predictions of neural networks based on the softmax activation layer. In existing work, this connection has been…
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering
Sibylle Hess, Wouter Duivesteijn, Philipp Honysz +1
When it comes to clustering nonconvex shapes, two paradigms are used to find the most suitable clustering: minimum cut and maximum density. The most popular algorithms incorporatin…
Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally
Oren Zeev-Ben-Mordehai, Wouter Duivesteijn, Mykola Pechenizkiy
Finding regions for which there is higher controversy among different classifiers is insightful with regards to the domain and our models. Such evaluation can falsify assumptions,…