Zobrazeno 1 - 10
of 514
pro vyhledávání: '"Bibas, P."'
Autor:
Bibas, Koby
Machine learning models have exhibited exceptional results in various domains. The most prevalent approach for learning is the empirical risk minimizer (ERM), which adapts the model's weights to reduce the loss on a training set and subsequently leve
Externí odkaz:
http://arxiv.org/abs/2412.07520
Autor:
Eleftheria Iliadou, Vasileios Bitzios, Konstantinos Pastiadis, Christopher J. Plack, Athanasios Bibas
Publikováno v:
Noise and Health, Vol 26, Iss 122, Pp 243-251 (2024)
Background: Use of noise or music in experimental human studies requires balancing the need to avoid subjecting participants to potentially harmful noise levels while still reaching levels that will produce a measurable change in the primary outcome.
Externí odkaz:
https://doaj.org/article/a3a19d98efea45a085043d8f96f706a8
Publikováno v:
Audiology Research, Vol 14, Iss 5, Pp 844-856 (2024)
Effective management of hearing loss through the use of modern hearing aids significantly improves communication and the quality of life for individuals experiencing auditory impairment. Complementary counselling of patients with hearing loss who wil
Externí odkaz:
https://doaj.org/article/697b36335b8f4cf096fae84693c74745
Complementary item recommendations are a ubiquitous feature of modern e-commerce sites. Such recommendations are highly effective when they are based on collaborative signals like co-purchase statistics. In certain online marketplaces, however, e.g.,
Externí odkaz:
http://arxiv.org/abs/2303.05812
Automatically understanding the contents of an image is a highly relevant problem in practice. In e-commerce and social media settings, for example, a common problem is to automatically categorize user-provided pictures. Nowadays, a standard approach
Externí odkaz:
http://arxiv.org/abs/2210.11907
Autor:
Isaac de Faria Soares Rodrigues, Paulo Francisco Guerreiro Cardoso, Natalia Aparecida Nepomuceno da Silva, Aristides Tadeu Correia, Helio Minamoto, Benoit Jacques Bibas, Natalia de Souza Xavier Costa, Marilia Wellichan Mancini, Marisa Dolhnikoff, Paulo Manuel Pego-Fernandes
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract To compare two different wavelengths of the surgical contact diode laser (CDL) for producing a posterior laryngofissure in in-vivo pigs. Anesthetized pigs underwent a tracheostomy and an anterior laryngofissure through a cervicotomy. They we
Externí odkaz:
https://doaj.org/article/819c6ebbfed64dd4a29e5febb62e9d9a
Autor:
Bibas, Koby, Feder, Meir
In supervised batch learning, the predictive normalized maximum likelihood (pNML) has been proposed as the min-max regret solution for the distribution-free setting, where no distributional assumptions are made on the data. However, the pNML is not d
Externí odkaz:
http://arxiv.org/abs/2206.08757
Autor:
Anne G. M. Schilder, Stephan Wolpert, Shakeel Saeed, Leonie M. Middelink, Albert S. B. Edge, Helen Blackshaw, REGAIN Consortium, Kostas Pastiadis, Athanasios G. Bibas
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-9 (2024)
Abstract Inhibition of Notch signalling with a gamma-secretase inhibitor (GSI) induces mammalian hair cell regeneration and partial hearing restoration. In this proof-of-concept Phase I/IIa multiple-ascending dose open-label trial (ISRCTN59733689), a
Externí odkaz:
https://doaj.org/article/c507482871e1458b9e7192e6aabb92b2
Detecting out-of-distribution (OOD) samples is vital for developing machine learning based models for critical safety systems. Common approaches for OOD detection assume access to some OOD samples during training which may not be available in a real-
Externí odkaz:
http://arxiv.org/abs/2110.09246
Publikováno v:
Mediterranean Journal of Hematology and Infectious Diseases, Vol 16, Iss 1 (2024)
Waldenström macroglobulinemia (WM) is an infrequent variant of lymphoma, classified as a B-cell malignancy identified by the presence of IgM paraprotein, infiltration of clonal, small lymphoplasmacytic B cells in the bone marrow, and the MYD88 L265P
Externí odkaz:
https://doaj.org/article/83e1a80094f944cb857c8ec0a5e73d97