Johannes Rausch — accepted AI-conference papers

2021

DocParser: Hierarchical Document Structure Parsing from Renderings

Johannes Rausch, Octavio Martinez, Fabian Bissig, Ce Zhang, Stefan Feuerriegel

AAAI 2021technical

Translating renderings (e. g. PDFs, scans) into hierarchical document structures is extensively demanded in the daily routines of many real-world applications. However, a holistic, principled approach to inferring the complete hierarchical structure in documents is missing. As a remedy, we developed…

Cited by 41 Source ↗PDF ↗code ↗Scholar ↗

2021

Online Active Model Selection for Pre-trained Classifiers

Mohammad Reza Karimi, Nezihe Merve Gürel, Bojan Karlaš, Johannes Rausch, Ce Zhang, Andreas Krause

AISTATS 2021poster

Given $k$ pre-trained classifiers and a stream of unlabeled data examples, how can we actively decide when to query a label so that we can distinguish the best model from the rest while making a small number of queries? Answering this question has a profound impact on a range of practical scenarios.…

Cited by 33 Source ↗PDF ↗code ↗Scholar ↗