Zobrazeno 1 - 10
of 6 793
pro vyhledávání: '"Zamboni, P"'
The problem of pure exploration in Markov decision processes has been cast as maximizing the entropy over the state distribution induced by the agent's policy, an objective that has been extensively studied. However, little attention has been dedicat
Externí odkaz:
http://arxiv.org/abs/2406.12795
Recent works have studied *state entropy maximization* in reinforcement learning, in which the agent's objective is to learn a policy inducing high entropy over states visitation (Hazan et al., 2019). They typically assume full observability of the s
Externí odkaz:
http://arxiv.org/abs/2406.02295
Recognized for their non-diffracting properties, Bessel beams can be conveniently combined to generate the so-called Frozen Waves, which are monochromatic beams endowed with topological charge and whose longitudinal intensity pattern can be shaped ac
Externí odkaz:
http://arxiv.org/abs/2402.02828
While in linear optics the subject of structured light has been a fruitful field of both theoretical and applied research, its development in the arena of nonlinear optics has been underexplored. In this paper, we construct Frozen-Wave-type structure
Externí odkaz:
http://arxiv.org/abs/2308.13763
Autor:
Antonella D’Ambrosio, Silvia Zamboni, Serena Camerini, Marialuisa Casella, Massimo Sanchez, Donatella Pietraforte, Nicola Vanacore, Marco Diociauti, Marta Altieri, Vittorio Di Piero, Ada Francia, Simona Pontecorvo, Marco Puthenparampil, Paolo Gallo, Paola Margutti
Publikováno v:
Journal of Neuroinflammation, Vol 21, Iss 1, Pp 1-20 (2024)
Abstract Background and objectives There is an urgent need to discover blood-based biomarkers of multiple sclerosis (MS) to better define the underlying biology of relapses and monitor disease progression. The main goal of this study is to search for
Externí odkaz:
https://doaj.org/article/ceaf8af294be45bda7e881e56739495a
A comparative analysis of classical and machine learning methods for forecasting TB/HIV co-infection
Autor:
André Abade, Lucas Faria Porto, Alessandro Rolim Scholze, Daniely Kuntath, Nathan da Silva Barros, Thaís Zamboni Berra, Antonio Carlos Vieira Ramos, Ricardo Alexandre Arcêncio, Josilene Dália Alves
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract TB/HIV coinfection poses a complex public health challenge. Accurate forecasting of future trends is essential for efficient resource allocation and intervention strategy development. This study compares classical statistical and machine lea
Externí odkaz:
https://doaj.org/article/93b53cc6f31e4c4db0a4396fc1f8079f
Autor:
Thaís Zamboni Berra, Yan Mathias Alves, Marcela Antunes Paschoal Popolin, Fernanda Bruzadelli Paulino da Costa, Reginaldo Bazon Vaz Tavares, Ariela Feh Tártaro, Heriederson Sávio Dias Moura, Letícia Perticarrara Ferezin, Monica Chiodi Toscano de Campos, Natacha Martins Ribeiro, Titilade Kehinde Ayandeyi Teibo, Rander Junior Rosa, Ricardo Alexandre Arcêncio
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Objective To assess the evolution of the COVID-19 pandemic in Brazil and its macro-regions, considering disease incidence and mortality rates, as well as identifying territories with still rising disease indices and evaluating vaccine covera
Externí odkaz:
https://doaj.org/article/155332b92f6047dfa72e0873b252f49e
Autor:
Ferenczi, Sébastien, Zamboni, Luca Q.
We characterize the clustering of a word under the Burrows-Wheeler transform in terms of the resolution of a bounded number of bispecial factors belonging to the language generated by all its powers. We use this criterion to compute, in every given A
Externí odkaz:
http://arxiv.org/abs/2305.18986
Autor:
Bocca, Simone, Zamboni, Alessio, Bella, Gabor, Chandrashekar, Yamini, Bagchi, Mayukh, Kuper, Gabriel, Bouquet, Paolo, Giunchiglia, Fausto
Publikováno v:
DSAI SPRINGER BOOK, 2023
When building a new application we are increasingly confronted with the need of reusing and integrating pre-existing knowledge. Nevertheless, it is a fact that this prior knowledge is virtually impossible to reuse as-is. This is true also in domains,
Externí odkaz:
http://arxiv.org/abs/2305.06088
Autor:
Goncalves, Diogo Nunes, Junior, Jose Marcato, Zamboni, Pedro, Pistori, Hemerson, Li, Jonathan, Nogueira, Keiller, Goncalves, Wesley Nunes
Multi-task learning has proven to be effective in improving the performance of correlated tasks. Most of the existing methods use a backbone to extract initial features with independent branches for each task, and the exchange of information between
Externí odkaz:
http://arxiv.org/abs/2305.02813