Zobrazeno 1 - 10
of 312
pro vyhledávání: '"Vangelis Karkaletsis"'
Publikováno v:
The Journal of Supercomputing. 79:10691-10705
HPC is a key tool for processing and analyzing the constantly growing volume of data, from 64.2 zettabytes in 2020 to an expected 180 zettabytes in 2025 (1 zettabyte is equal to 1 trillion gigabytes). As such, HPC has a large number of application ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b6226ffe3ea0272154199b2d82103cbe
https://doi.org/10.1007/s11227-023-05080-y
https://doi.org/10.1007/s11227-023-05080-y
Publikováno v:
Open Journal of Social Sciences. 11:313-338
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::195d1b09c265b81732eb34a4c008683b
https://doi.org/10.4236/jss.2023.113023
https://doi.org/10.4236/jss.2023.113023
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 16:1-22
Unsupervised representation learning tends to produce generic and reusable latent representations. However, these representations can often miss high-level features or semantic information, since they only observe the implicit properties of the datas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4bc9849f9905fb5e35cdb6996e45b7cf
https://doi.org/10.1145/3502732
https://doi.org/10.1145/3502732
Autor:
Christos Sevastopoulos, Michail Theofanidis, Mohammad Zaki Zadeh, Sneh Acharya, Stasinos Konstantopoulos, Vangelis Karkaletsis, Fillia Makedon
Publikováno v:
2022 Sixth IEEE International Conference on Robotic Computing (IRC).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f975a943480b8e326d0718e8ada2adc5
https://doi.org/10.1109/irc55401.2022.00059
https://doi.org/10.1109/irc55401.2022.00059
Publikováno v:
Informatics, Vol 6, Iss 2, p 17 (2019)
Evidence transfer for clustering is a deep learning method that manipulates the latent representations of an autoencoder according to external categorical evidence with the effect of improving a clustering outcome. Evidence transfer’s application o
Externí odkaz:
https://doaj.org/article/498dacfa6ff44720ad13a5ccfa971de8
Publikováno v:
Technologies, Vol 6, Iss 4, p 119 (2018)
In this article, we present a taxonomy in Robot-Assisted Training; a growing body of research in Human⁻Robot Interaction which focuses on how robotic agents and devices can be used to enhance user’s performance during a cognitive or physical trai
Externí odkaz:
https://doaj.org/article/9aba0fb33a65405e91e321d5cf04192e
Publikováno v:
Digital Culture & Education, Vol 8, Iss 2 (2016)
The process of effectively applying techniques for fostering creativity in educational settings is – by nature – multifaceted and not straightforward, as it pertains to several fields such as cognitive theory and psychology. Furthermore, the quan
Externí odkaz:
https://doaj.org/article/d61123bb088346e3a562b3e508ad25bb
Autor:
Michael Huebner, Maria Dagioglou, Diana Goehringer, Nikolaos S. Voros, Christos P. Antonopoulos, Stasinos Konstantopoulos, Georgios Keramidas, Vangelis Karkaletsis, Fynn Schwiegelshohn, Georgios Stavrinos
Publikováno v:
IEEE Consumer Electronics Magazine. 9:77-82
Health care platforms rapidly shift toward the ICT-based solutions. In this context, a wide range of consumer electronics technologies come into play ranging from robotics, embedded systems, sensors, and communication infrastructures. Driven by such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::888132e074510530e6f79b2dae5302c7
https://doi.org/10.1109/mce.2020.2969202
https://doi.org/10.1109/mce.2020.2969202
Publikováno v:
Natural Language Engineering. 27:391-425
The recent breakthroughs in deep neural architectures across multiple machine learning fields have led to the widespread use of deep neural models. These learners are often applied as black-box models that ignore or insufficiently utilize a wealth of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e89f3832f6eeb0b07ca3dc2cd89b6611
https://doi.org/10.1017/s1351324920000170
https://doi.org/10.1017/s1351324920000170
Publikováno v:
PETRA
In domains such as Human-Robot Collaboration artificial agents must be able to support mutual adaptation and learning. Towards this direction, we use a discrete Soft Actor-Critic agent on a real-time collaborative game with humans. We examine how dif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cd9172c47edb44b24cfa853c02765ac7
https://doi.org/10.1145/3453892.3454004
https://doi.org/10.1145/3453892.3454004