Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Marcin Sendera"'
Autor:
Marcin Sendera, Marcin Przewiȩźlikowski, Jan Miksa, Mateusz Rajski, Konrad Karanowski, Maciej Ziȩba, Jacek Tabor, Przemysław Spurek
Publikováno v:
Machine Vision and Applications. 34
Few-shot models aim at making predictions using a minimal number of labeled examples from a given task. The main challenge in this area is the one-shot setting, where only one element represents each class. We propose the general framework for few-sh
Autor:
Lukasz Struski, Jacek Tabor, Marcin Sendera, Marek Smieja, Przemysław Spurek, Lukasz Maziarka
Publikováno v:
IEEE transactions on pattern analysis and machine intelligence. 44(11)
We propose OneFlow - a flow-based one-class classifier for anomaly (outlier) detection that finds a minimal volume bounding region. Contrary to density-based methods, OneFlow is constructed in such a way that its result typically does not depend on t
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030923068
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::495ffa537c14bc707487670f94ffc6d4
https://ruj.uj.edu.pl/xmlui/handle/item/285134
https://ruj.uj.edu.pl/xmlui/handle/item/285134
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030504328
ICCS (6)
Computational Science – ICCS 2020
ICCS (6)
Computational Science – ICCS 2020
Data assimilation (DA) is a key procedure that synchronizes a computer model with real observations. However, in the case of overparametrized complex systems modeling, the task of parameter-estimation through data assimilation can expand exponentiall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4444305954ec788b4716004eb74f09c2
https://doi.org/10.1007/978-3-030-50433-5_11
https://doi.org/10.1007/978-3-030-50433-5_11
Autor:
Marcin Sendera, Adam Szlachta, Aleksander Byrski, Mateusz Paciorek, Marek Kisiel-Dorohinicki, Leszek Placzkiewicz, Mateusz Godzik
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319937007
ICCS (2)
ICCS (2)
In this paper a novel hybridization of agent-based evolutionary system (EMAS, a metaheuristic putting together agency and evolutionary paradigms) is presented. This method assumes utilization of particle swarm optimization (PSO) for upgrading certain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::378964ac1cd59e89d63eba8af127e5c9
https://doi.org/10.1007/978-3-319-93701-4_7
https://doi.org/10.1007/978-3-319-93701-4_7