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pro vyhledávání: '"Lee, Loong Kuan"'
Autor:
Lee, Loong Kuan, Knaute, Johannes, Gerhardt, Florian, Völker, Patrick, Maras, Tomislav, Dotterweich, Alexander, Piatkowski, Nico
Adiabatic quantum computation (AQC) is a well-established method to approximate the ground state of a quantum system. Actual AQC devices, known as quantum annealers, have certain limitations regarding the choice of target Hamiltonian. Specifically, t
Externí odkaz:
http://arxiv.org/abs/2409.09857
The ability to compute the exact divergence between two high-dimensional distributions is useful in many applications but doing so naively is intractable. Computing the alpha-beta divergence -- a family of divergences that includes the Kullback-Leibl
Externí odkaz:
http://arxiv.org/abs/2310.09129
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 37, 10 (Jun. 2023), 12243-12251
There are many applications that benefit from computing the exact divergence between 2 discrete probability measures, including machine learning. Unfortunately, in the absence of any assumptions on the structure or independencies within these distrib
Externí odkaz:
http://arxiv.org/abs/2112.04583
Akademický článek
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Concept drift is a major issue that greatly affects the accuracy and reliability of many real-world applications of machine learning. We argue that to tackle concept drift it is important to develop the capacity to describe and analyze it. We propose
Externí odkaz:
http://arxiv.org/abs/1704.00362
Autor:
LEE, LOONG KUAN
When the underlying distribution of a stream of incoming data changes, existing models trained on previous data may degrade in performance. Known as concept drift, one way to characterise these changes, is by measuring the magnitude at which these di
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82aca4ba17f05e9821344a34c11f34b0
Akademický článek
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