Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Martin Plajner"'
Autor:
Theodor Petřík, Martin Plajner
Publikováno v:
Ekonomski Vjesnik, Vol 37, Iss 1, Pp 139-150 (2024)
Purpose: This article introduces an innovative method designed to optimize distribution strategies with respect to future uncertainty. It goes beyond the limitations of traditional scenario-based planning that often leads to suboptimal strategies due
Externí odkaz:
https://doaj.org/article/a948a076ce5c404ca8ce07d3900ed6ee
Autor:
Jiří Vomlel, Martin Plajner
Publikováno v:
International Journal of General Systems. 49:88-111
Learning parameters of a probabilistic model is a necessary step in machine learning tasks. We present a method to improve learning from small datasets by using monotonicity conditions. Monotonicit...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5905472abce0d1947be6ce128b21c285
https://doi.org/10.1080/03081079.2019.1692004
https://doi.org/10.1080/03081079.2019.1692004
Autor:
Jiří Vomlel, Martin Plajner
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030867713
ECSQARU
ECSQARU
In this paper we study the problem of student knowledge level estimation. We use probabilistic models learned from collected data to model the tested students. We propose and compare experimentally several different Bayesian network models for the sc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7db261f9f06e25fb36e3d2f8d7dfe15d
https://doi.org/10.1007/978-3-030-86772-0_19
https://doi.org/10.1007/978-3-030-86772-0_19
Autor:
Martin Plajner, Jiří Vomlel
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319615806
ECSQARU
ECSQARU
Artificial intelligence is present in many modern computer science applications. The question of effectively learning parameters of such models even with small data samples is still very active. It turns out that restricting conditional probabilities
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31b9f924d5a20cb4d705176c62c976a2
https://doi.org/10.1007/978-3-319-61581-3_12
https://doi.org/10.1007/978-3-319-61581-3_12