25 citations · 44 across the 7 of their papers we have counts for
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cs.LG2019
k is the Magic Number -- Inferring the Number of Clusters Through Nonparametric Concentration Inequalities
Sibylle Hess, Wouter Duivesteijn
Most convex and nonconvex clustering algorithms come with one crucial parameter: the in -means. To this day, there is not one generally accepted way to accurately determine…
cs.LG2019
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…
cs.LG2019★ 25 cited
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data
Xin Du, Lei Sun, Wouter Duivesteijn +2
Learning causal effects from observational data greatly benefits a variety of domains such as health care, education and sociology. For instance, one could estimate the impact of a…