Zobrazeno 1 - 10
of 129
pro vyhledávání: '"Thiele Maik"'
Publikováno v:
International Journal of Applied Mathematics and Computer Science, Vol 29, Iss 1, Pp 69-79 (2019)
Today’s ETL tools provide capabilities to develop custom code as user-defined functions (UDFs) to extend the expressiveness of the standard ETL operators. However, while this allows us to easily add new functionalities, it also comes with the risk
Externí odkaz:
https://doaj.org/article/26067912ad9c47aabd386140ea3846f0
Autor:
Gonsior, Julius, Falkenberg, Christian, Magino, Silvio, Reusch, Anja, Thiele, Maik, Lehner, Wolfgang
Despite achieving state-of-the-art results in nearly all Natural Language Processing applications, fine-tuning Transformer-based language models still requires a significant amount of labeled data to work. A well known technique to reduce the amount
Externí odkaz:
http://arxiv.org/abs/2210.03005
Active Learning (AL) is a well-known standard method for efficiently obtaining annotated data by first labeling the samples that contain the most information based on a query strategy. In the past, a large variety of such query strategies has been pr
Externí odkaz:
http://arxiv.org/abs/2208.11636
One of the biggest challenges that complicates applied supervised machine learning is the need for huge amounts of labeled data. Active Learning (AL) is a well-known standard method for efficiently obtaining labeled data by first labeling the samples
Externí odkaz:
http://arxiv.org/abs/2108.07670
Processing and analyzing time series data\-sets have become a central issue in many domains requiring data management systems to support time series as a native data type. A crucial prerequisite of these systems is time series matching, which still i
Externí odkaz:
http://arxiv.org/abs/2105.14867
There are massive amounts of textual data residing in databases, valuable for many machine learning (ML) tasks. Since ML techniques depend on numerical input representations, word embeddings are increasingly utilized to convert symbolic representatio
Externí odkaz:
http://arxiv.org/abs/1911.12674
Modern big data frameworks (such as Hadoop and Spark) allow multiple users to do large-scale analysis simultaneously. Typically, users deploy Data-Intensive Workflows (DIWs) for their analytical tasks. These DIWs of different users share many common
Externí odkaz:
http://arxiv.org/abs/1806.03901
Akademický článek
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Open data platforms such as data.gov or opendata.socrata. com provide a huge amount of valuable information. Their free-for-all nature, the lack of publishing standards and the multitude of domains and authors represented on these platforms lead to n
Externí odkaz:
http://arxiv.org/abs/1205.2465
Spreadsheets are very successful content generation tools, used in almost every enterprise to create a wealth of information. However, this information is often intermingled with various formatting, layout, and textual metadata, making it hard to ide
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82970
https://tud.qucosa.de/api/qucosa%3A82970/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82970/attachment/ATT-0/