Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Kinga Siuta"'
Autor:
Ashkan Dehghan, Kinga Siuta, Agata Skorupka, Akshat Dubey, Andrei Betlen, David Miller, Wei Xu, Bogumił Kamiński, Paweł Prałat
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-37 (2023)
Abstract Users on social networks such as Twitter interact with each other without much knowledge of the real-identity behind the accounts they interact with. This anonymity has created a perfect environment for bot accounts to influence the network
Externí odkaz:
https://doaj.org/article/f20592c1c8bc436d980b2440e710dfad
Autor:
Ashkan Dehghan, Kinga Siuta, Agata Skorupka, Andrei Betlen, David Miller, Bogumił Kamiński, Paweł Prałat
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031322952
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f357dd2c66bd39086d5e7cf98d2a76c8
https://doi.org/10.1007/978-3-031-32296-9_3
https://doi.org/10.1007/978-3-031-32296-9_3
Autor:
Kinga Siuta, Daniel Kaszyński
Publikováno v:
Control and Cybernetics. 50:195-221
This research deals with a phenomenon well-known in socio-economic studies and referred to as the Agency Theory: the principal-agent problem. The agent is designated to act on behalf of the company owner, i.e., the principal, in the domain of supply
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::545c1c6846ebad76f4130ba915a1138a
https://doi.org/10.2478/candc-2021-0011
https://doi.org/10.2478/candc-2021-0011
Autor:
Ashkan Dehghan, Kinga Siuta, Agata Skorupka, Akshat Dubey, Andrei Betlen, David Miller, Wei Xu, Bogumił Kamiński, Paweł Prałat
Users on social networks such as Twitter interact with and are influenced by each other without much knowledge of the identity behind each user. This anonymity has created a perfect environment for bot and hostile accounts to influence the network by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e0f0480142d9e29e52f79e17e2f84d5
https://doi.org/10.21203/rs.3.rs-1428343/v1
https://doi.org/10.21203/rs.3.rs-1428343/v1
Autor:
Daniel Kaszyński, Bogumił Kamiński, Tomasz Szapiro, Maciej Kwiatkowski, Karol Przanowski, Sebastian Zając, Łukasz Opiński, Małgorzata Wrzosek, Kinga Siuta, Kamil Cerazy, Marcin Chlebus, Marta Kłosok, Przemysław Biecek, Łukasz Kraiński, Aleksander Nosarzewski
The volume Credit scoring in context of interpretable machine learning presents a unique, and simultaneously balanced, combination of explanation of theoretical concepts and contemporary scoring practices rooted in these concepts. We assume that the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::47011b090594c931700bb22a73f94948