4 papers
Overlapped We Stand, Separated We Fall: Software Approaches to Diagnosing Separation Phenomena in Categorical Response Models
Thomas Rusch, Lukas Sablica, Kurt Hornik
In statistical models for categorical responses, including binary, nominal and ordinal responses, a phenomenon called ``separation'' may occur which can render maximum likelihood e…
The Geometry of Existence and Uniqueness of Maximum Likelihood Estimation in Categorical Response Models
Lukas Sablica, Kurt Hornik, Thomas Rusch
Nonexistence of the maximum likelihood estimate (MLE) under separation is treated as a solved problem for binary logistic regression and as a scattered collection of model-specific…
Spherical Cauchy Variational Autoencoders: Heavy Angular Tails and Exact KL Evaluation
Lukas Sablica, Kurt Hornik
Heavy-tailed posteriors are routine in Euclidean variational autoencoders, where the Student family relaxes the Gaussian without new machinery. The sphere has had no comparable opt…
Named Entity Swapping for Metadata Anonymization in a Text Corpus
Jan Greve, Lukas Sablica
This work introduces an anonymization scheme for a corpus of texts to safeguard metadata from disclosure. It specifically aims to prevent large language models from identifying met…