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pro vyhledávání: '"Rausch, Johannes"'
Information in industry, research, and the public sector is widely stored as rendered documents (e.g., PDF files, scans). Hence, to enable downstream tasks, systems are needed that map rendered documents onto a structured hierarchical format. However
Externí odkaz:
http://arxiv.org/abs/2310.09118
Tables have been an ever-existing structure to store data. There exist now different approaches to store tabular data physically. PDFs, images, spreadsheets, and CSVs are leading examples. Being able to parse table structures and extract content boun
Externí odkaz:
http://arxiv.org/abs/2201.01654
Autor:
Rausch, Johannes1 (AUTHOR) rausch@med.uni-frankfurt.de, Steinbicker, Andrea U.1 (AUTHOR), Friedrichson, Benjamin1 (AUTHOR), Flinspach, Armin N.1 (AUTHOR), Zacharowski, Kai1 (AUTHOR), Adam, Elisabeth H.1 (AUTHOR), Piekarski, Florian1,2 (AUTHOR)
Publikováno v:
Journal of Clinical Medicine. Jul2024, Vol. 13 Issue 14, p4081. 10p.
Autor:
Rausch, Johannes1, Börsch-Supan, Axel1
Publikováno v:
ifo Schnelldienst. mai2024, Vol. 77 Issue 5, p63-72. 10p.
Autor:
Karimi, Mohammad Reza, Gürel, Nezihe Merve, Karlaš, Bojan, Rausch, Johannes, Zhang, Ce, Krause, Andreas
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
Externí odkaz:
http://arxiv.org/abs/2010.09818
Federated learning (FL) is a popular technique to train machine learning (ML) models on decentralized data sources. In order to sustain long-term participation of data owners, it is important to fairly appraise each data source and compensate data ow
Externí odkaz:
http://arxiv.org/abs/2009.06192
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
Externí odkaz:
http://arxiv.org/abs/1911.01702
Publikováno v:
NBER Working Papers; Aug2024, Issue 32785-32859, p1-58, 58p
Publikováno v:
NBER Working Papers; Aug2024, Issue 32785-32859, p1-30, 30p
Autor:
Rausch, Johannes1 rausch@mea.mpisoc.mpg.de
Publikováno v:
Perspektiven der Wirtschaftspolitik. Sep2023, Vol. 24 Issue 3, p332-360. 29p.