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Ilia Zaznov, Julian Martin Kunkel, Atta Badii and Alfonso Dufour
This paper introduces a novel deep learning approach for intraday stock price direction prediction, motivated by the need for more accurate models to enable profitable algorithmic trading. The key problems addressed are effectively modelling complex limi...
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Jonathan Decker, Piotr Kasprzak and Julian Martin Kunkel
Serverless computing has grown massively in popularity over the last few years, and has provided developers with a way to deploy function-sized code units without having to take care of the actual servers or deal with logging, monitoring, and scaling of ...
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Julian Martin Kunkel,Anastasiia Novikova,Eugen Betke
Pág. 17 - 33
Data intense scientific domains use data compression to reduce the storage space needed. Lossless data compression preserves information accurately but lossy data compression can achieve much higher compression rates depending on the tolerable error marg...
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Julian Martin Kunkel
Pág. 34 - 39
Understanding the characteristics of data stored in data centers helps computer scientists in identifying the most suitable storage infrastructure to deal with these workloads. For example, knowing the relevance of file formats allows optimizing the rele...
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Julian Martin Kunkel,Michael Kuhn,Thomas Ludwig
Pág. 116 - 134
The computational power and storage capability of supercomputers are growing at a different pace, with storage lagging behind; the widening gap necessitates new approaches to keep the investment and running costs for storage systems at bay. In this paper...
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