Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Hartmann, Claudio"'
The results of the presented work show that machine learning (ML) can be used to support correct training logging in order to improve technical performance in trampoline gymnastics. They indicate considerable potential for expanding mobile applicatio
The task of the judge of difficulty in trampoline gymnastics is to check the elements and difficulty values entered on the competition cards and the difficulty of each element according to a numeric system. To do this, the judge must count all somers
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A89530
https://tud.qucosa.de/api/qucosa%3A89530/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A89530/attachment/ATT-0/
Cardinality estimation is a fundamental task in database query processing and optimization. As shown in recent papers, machine learning (ML)-based approaches may deliver more accurate cardinality estimations than traditional approaches. However, a lo
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A89177
https://tud.qucosa.de/api/qucosa%3A89177/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A89177/attachment/ATT-0/
Cardinality estimation is a fundamental task in database query processing and optimization. Unfortunately, the accuracy of traditional estimation techniques is poor resulting in non-optimal query execution plans. With the recent expansion of machine
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A79467
https://tud.qucosa.de/api/qucosa%3A79467/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A79467/attachment/ATT-0/
The forecasting of time series data is an integral component for management, planning, and decision making. Following the Big Data trend, large amounts of time series data are available in many application domains. The highly dynamic and often noisy
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82181
https://tud.qucosa.de/api/qucosa%3A82181/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82181/attachment/ATT-0/
More and more data is gathered every day and time series are a major part of it. Due to the usefulness of this type of data, it is analyzed in many application domains. While there already exists a broad variety of methods for this task, there is sti
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A86040
https://tud.qucosa.de/api/qucosa%3A86040/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A86040/attachment/ATT-0/
Autor:
Meyer, Holger J., Gruner, Hannes, Waizenegger, Tim, Woltmann, Lucas, Hartmann, Claudio, Lehner, Wolfgang, Esmailoghli, Mahdi, Redyuk, Sergey, Martinez, Ricardo, Abedjan, Ziawasch, Ziehn, Ariane, Rabl, Tilmann, Markl, Volker, Schmitz, Christian, Serai, Dhiren Devinder, Gava, Tatiane Escobar
For the second time, the Data Science Challenge took place as part of the 18th symposium “Database Systems for Business, Technology and Web” (BTW) of the Gesellschaft für Informatik (GI). The Challenge was organized by the University of Rostock
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A86038
https://tud.qucosa.de/api/qucosa%3A86038/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A86038/attachment/ATT-0/
The role of precise forecasts in the energy domain has changed dramatically. New supply forecasting methods are developed to better address this challenge, but meaningful benchmarks are rare and time-intensive. We propose the ECAST online platform in
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80740
https://tud.qucosa.de/api/qucosa%3A80740/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80740/attachment/ATT-0/
Forecasting time series data is an integral component for management, planning and decision making. Following the Big Data trend, large amounts of time series data are available from many heterogeneous data sources in more and more applications domai
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82105
https://tud.qucosa.de/api/qucosa%3A82105/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82105/attachment/ATT-0/
Predicting time series is a crucial task for organizations, since decisions are often based on uncertain information. Many forecasting models are designed from a generic statistical point of view. However, each real-world application requires domain-
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A81155
https://tud.qucosa.de/api/qucosa%3A81155/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A81155/attachment/ATT-0/