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description Publicationkeyboard_double_arrow_right Preprint , Report , Article , Other literature type 2024 SwedenPublisher:Elsevier BV Funded by:UKRI | UAS Authentication Servic..., ANR | PGSEUKRI| UAS Authentication Service (UASAS) ,ANR| PGSEAuthors: Grenet, Julien; Grönqvist, Hans; Niknami, Susan;Grenet, Julien; Grönqvist, Hans; Niknami, Susan;Electronic monitoring (EM) has emerged as a popular tool for curbing the growth of large prison populations. Evidence on the causal effects of EM on criminal recidivism is, however, limited and it is unclear how this alternative to incarceration affects the labor supply of offenders and the outcomes of their family members. We study the country wide expansion of EM in Sweden in 1997 where in offenders sentenced to up to three months in prison were granted the option to substitute incarceration with EM. Our difference-in-differences estimates, which compare the change in the prison inflow rate of treated offenders to that of non-treated offenders with slightly longer sentences, show that the reform significantly decreased the number of incarcerations. Our main finding is that EM not only lowers criminal recidivism but also increases labor supply. Additionally, EM improves the educational attainment and early-life earnings of the children whose parents were exposed to the reform. The primary mechanisms through which EM operates appear to involve the preservation of offenders’ ties to the labor market, by reducing the barriers to both finding a job and changing employers. Our calculations suggest that the social benefits stemming from EM are about seven times larger than the fiscal savings associated with reduced prison expenditures, implying that the welfare gains from EM could be much greater than previously acknowledged.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jpubeco.2023.105051&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jpubeco.2023.105051&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Report , Other literature type 2023 FrancePublisher:Zenodo Authors: Raevskikh, Elena; Khalid, Usman; Pinto, Jorge;Raevskikh, Elena; Khalid, Usman; Pinto, Jorge;This report is the first statistical overview of the share of the culture sector in Abu Dhabi’s GDP (Gross Domestic Product). The analysis is based on the Statistics Centre Abu Dhabi (SCAD) Annual Economic Survey data available for the 2005–20 period. The approach to the data analysis has been harmonised through a leading international benchmark in culture statistics, the Eurostat ESS-Net Culture framework.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Report 2023 FrancePublisher:Zenodo Authors: Raevskikh, Elena; Pinto, Jorge; Khalid, Usman;Raevskikh, Elena; Pinto, Jorge; Khalid, Usman;This report is the first statistical overview of the exports and imports of cultural goods in Abu Dhabi. The analysis is based on Statistics Centre Abu Dhabi (SCAD) data available for the 2014– 20 period and data from Abu Dhabi Chamber of Commerce and Industry (ADCCI) Certificates of Origin (2020). The approach to the data analysis has been harmonised with a leading international benchmark in culture statistics — the Eurostat ESS-Net Culture framework.
ZENODO arrow_drop_down Hyper Article en Ligne; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Report . 2021License: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404232&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert ZENODO arrow_drop_down Hyper Article en Ligne; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Report . 2021License: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404232&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint , Report , Other literature type 2023 France, GermanyPublisher:Society for Industrial & Applied Mathematics (SIAM) Funded by:EC | SYSTEMATICGRAPH, ANR | DISTANCIAEC| SYSTEMATICGRAPH ,ANR| DISTANCIAJérémie Chalopin; Victor Chepoi; Fionn Mc Inerney; Sébastien Ratel; Yann Vaxès;One of the open problems in machine learning is whether any set-family of VC-dimension $d$ admits a sample compression scheme of size~$O(d)$. In this paper, we study this problem for balls in graphs. For balls of arbitrary radius $r$, we design proper sample compression schemes of size $2$ for trees, of size $3$ for cycles, of size $4$ for interval graphs, of size $6$ for trees of cycles, and of size $22$ for cube-free median graphs. For balls of a given radius, we design proper labeled sample compression schemes of size $2$ for trees and of size $4$ for interval graphs. We also design approximate sample compression schemes of size 2 for balls of $\delta$-hyperbolic graphs. Comment: 26 pages, 9 figures
arXiv.org e-Print Ar... arrow_drop_down Dagstuhl Research Online Publication ServerOther literature type . 2022License: CC BYData sources: Dagstuhl Research Online Publication ServerHAL AMU; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2022License: CC BYFull-Text: https://hal.science/hal-03854487/documenthttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1137/22m1527817&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down Dagstuhl Research Online Publication ServerOther literature type . 2022License: CC BYData sources: Dagstuhl Research Online Publication ServerHAL AMU; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2022License: CC BYFull-Text: https://hal.science/hal-03854487/documenthttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1137/22m1527817&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Report , Other literature type , Preprint 2023 FrancePublisher:Elsevier BV Funded by:EC | MAJORISEC| MAJORISAuthors: Yunshi Huang; Emilie Chouzenoux; Víctor Elvira; Jean-Christophe Pesquet;Yunshi Huang; Emilie Chouzenoux; Víctor Elvira; Jean-Christophe Pesquet;International audience; Bayesian neural networks (BNNs) have received an increased interest in the last years. In BNNs, a complete posterior distribution of the unknown weight and bias parameters of the network is produced during the training stage. This probabilistic estimation offers several advantages with respect to point-wise estimates, in particular, the ability to provide uncertainty quantification when predicting new data. This feature inherent to the Bayesian paradigm, is useful in countless machine learning applications. It is particularly appealing in areas where decision-making has a crucial impact, such as medical healthcare or autonomous driving. The main challenge of BNNs is the computational cost of the training procedure since Bayesian techniques often face a severe curse of dimensionality. Adaptive importance sampling (AIS) is one of the most prominent Monte Carlo methodologies benefiting from sounded convergence guarantees and ease for adaptation. This work aims to show that AIS constitutes a successful approach for designing BNNs. More precisely, we propose a novel algorithm named PMCnet that includes an efficient adaptation mechanism, exploiting geometric information on the complex (often multimodal) posterior distribution. Numerical results illustrate the excellent performance and the improved exploration capabilities of the proposed method for both shallow and deep neural networks.
Hyper Article en Lig... arrow_drop_down Journal of the Franklin InstituteArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jfranklin.2023.08.044&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down Journal of the Franklin InstituteArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jfranklin.2023.08.044&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Report , Preprint 2023 ItalyPublisher:Elsevier BV Funded by:UKRI | Enabling rapid adoption o..., EC | MINOAUKRI| Enabling rapid adoption of artificial intelligence through an anonymized data protocol and explainable models ,EC| MINOAAuthors: Renan Spencer Trindade; Claudia D'Ambrosio; Antonio Frangioni; Claudio Gentile;Renan Spencer Trindade; Claudia D'Ambrosio; Antonio Frangioni; Claudio Gentile;handle: 11568/1212787
Our study is motivated by the solution of Mixed-Integer Non-Linear Programming (MINLP) problems with separable non-convex functions via the Sequential Convex MINLP technique, an iterative method whose main characteristic is that of solving, for bounding purposes, piecewise-convex MINLP relaxations obtained by identifying the intervals in which each univariate function is convex or concave and then relaxing the concave parts with piecewise-linear relaxations of increasing precision. This process requires the introduction of new binary variables for the activation of the intervals where the functions are defined. In this paper we compare the three different standard formulations for the lower bounding subproblems and we show, both theoretically and computationally, that -- unlike in the piecewise-linear case -- they are not equivalent when the perspective reformulation is applied to reinforce the formulation in the segments where the original functions are convex.
arXiv.org e-Print Ar... arrow_drop_down Operations Research LettersArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Article . 2022 . 2023Archivio della Ricerca - Università di PisaArticle . 2023Data sources: Archivio della Ricerca - Università di Pisahttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.orl.2023.11.003&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down Operations Research LettersArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Article . 2022 . 2023Archivio della Ricerca - Università di PisaArticle . 2023Data sources: Archivio della Ricerca - Università di Pisahttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.orl.2023.11.003&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Report , Other literature type 2023 FrancePublisher:IEEE Minh, Céline; Vermeulen, Kevin; Lefebvre, Cédric; Owezarski, Philippe; Ritchie, William;International audience; Machine learning (ML) is a promising technology for network intrusion detection systems. There is a wide range of ML algorithms that are potential candidates for network intrusion detection systems, as they exhibit very good detection accuracy in average. However, significant detection differences appear when facing different kinds of attacks, some being prone to better detect some particular attack types. They then often appear to complement each other. The challenge then lies in determining the accurate result when several ML models provide different results, and this without any explanation about their decision. To address this challenge, our system aims to reconstruct attack patterns from the outputs of these ML models and presenting them in an interpretable manner. For that, we propose an approach combining ensemble learning and stacking with a meta-learner that works on graphical representation of traffic flows, that then provides the required explainability level for the decisions made. The evaluation of our system, using the CSE-CIC-IDS2018 dataset, demonstrates a significant improvement achieved through the combination of multiple ML algorithms. Furthermore, we emphasize the importance of explainability in network intrusion detection systems and the need for accurate and interpretable models. Our system goes beyond traditional detection methods by reporting anomalous feature pairs and providing visual representations of attack patterns, empowering analysts to better understand and respond to network threats.
Hyper Article en Lig... arrow_drop_down https://doi.org/10.23919/cnsm5...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: CrossrefMémoires en Sciences de l'Information et de la Communication; HAL-INSA ToulouseConference object . 2023Full-Text: https://hal.science/hal-04228893/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23919/cnsm59352.2023.10327818&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down https://doi.org/10.23919/cnsm5...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: CrossrefMémoires en Sciences de l'Information et de la Communication; HAL-INSA ToulouseConference object . 2023Full-Text: https://hal.science/hal-04228893/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23919/cnsm59352.2023.10327818&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Report , Other literature type 2023 Belgium, FrancePublisher:Springer Science and Business Media LLC Robert John Kolesar; Guido Erreygers; Wim Van Damme; Vanara Chea; Theany Choeurng; Soklong Leng;pmid: 37805483
pmc: PMC10559627
Abstract Background Financial risk protection is a core dimension of universal health coverage. Hardship financing, defined as borrowing and selling land or assets to pay for healthcare, is a measure of last recourse. Increasing indebtedness and high interest rates, particularly among unregulated money lenders, can lead to a vicious cycle of poverty and exacerbate inequity. Methods To inform efforts to improve Cambodia’s social health protection system we analyze 2019–2020 Cambodia Socio-economic Survey data to assess hardship financing, illness and injury related productivity loss, and estimate related economic impacts. We apply two-stage Instrumental Variable multiple regression to address endogeneity relating to net income. In addition, we calculate a direct economic measure to facilitate the regular monitoring and reporting on the devastating burden of excessive out-of-pocket expenditure for policy makers. Results More than 98,500 households or 2.7% of the total population resorted to hardship financing over the past year. Factors significantly increasing risk are higher out-of-pocket healthcare expenditures, illness or injury related productivity loss, and spending of savings. The economic burden from annual lost productivity from illness or injury amounts to US$ 459.9 million or 1.7% of GDP. The estimated household economic cost related to hardship financing is US$ 250.8 million or 0.9% of GDP. Conclusions Such losses can be mitigated with policy measures such as linking a catastrophic health coverage mechanism to the Health Equity Funds, capping interest rates on health-related loans, and using loan guarantees to incentivize microfinance institutions and banks to refinance health-related, high-interest loans from money lenders. These measures could strengthen social health protection by enhancing financial risk protection, mitigating vulnerability to the devastating economic effects of health shocks, and reducing inequities.
International Journa... arrow_drop_down Institutional Repository Universiteit AntwerpenReport . 2021Data sources: Institutional Repository Universiteit AntwerpenInstitutional Repository Universiteit AntwerpenArticle . 2023Data sources: Institutional Repository Universiteit AntwerpenInternational Journal for Equity in HealthArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12939-023-02016-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert International Journa... arrow_drop_down Institutional Repository Universiteit AntwerpenReport . 2021Data sources: Institutional Repository Universiteit AntwerpenInstitutional Repository Universiteit AntwerpenArticle . 2023Data sources: Institutional Repository Universiteit AntwerpenInternational Journal for Equity in HealthArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12939-023-02016-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 FrancePublisher:Elsevier BV Authors: Pooja Gupta; Angshul Majumdar; Emilie Chouzenoux; Giovanni Chierchia;Pooja Gupta; Angshul Majumdar; Emilie Chouzenoux; Giovanni Chierchia;International audience; In Drug-Drug-Interaction (DDI), the task is to predict the (adverse) effect of administering two drugs simultaneously. Currently, the techniques proposed in this direction are generally based on either shallow learning paradigms like Random Decision Forest (RDF), Logistic Regression (LR), Support Vector Machines (SVM), etc., or deep Convolutional Neural Networks (CNNs). However, specific works combine traditional machine learning (ML) algorithms such as RDF, LR, SVM, and deep learning paradigms such as CNNs in a piecemeal fashion which might not be optimal. Hence, the present work proposes a framework that presents a joint end-to-end solution. We propose a Siamese-like architecture with two processing channels' networks based on deep convolutional transform learning. Common fused representations as well as channel-wise representations are learnt, in addition with the transform across them. The final representation is passed to a decision forest to give final predictions. The proposed method is thus a supervised end-to-end multi-channel fusion framework that (i) learns unique and interpretable filters in contrast with CNNs, and (ii) jointly learns and optimizes decision forest in contrast with state-of-the-art piecemeal approach. We apply this technique to identify DDIs among 1059 drugs from the DrugBank database showing superiority of our method compared to the state-of-the-art(s).
INRIA a CCSD electro... arrow_drop_down INRIA a CCSD electronic archive server; Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationReport . Other literature type . 2022Full-Text: https://hal.science/hal-03897934/documentExpert Systems with ApplicationsArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.eswa.2023.120238&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu2 citations 2 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert INRIA a CCSD electro... arrow_drop_down INRIA a CCSD electronic archive server; Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationReport . Other literature type . 2022Full-Text: https://hal.science/hal-03897934/documentExpert Systems with ApplicationsArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.eswa.2023.120238&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Report , Other literature type 2023 FrancePublisher:Springer Science and Business Media LLC Funded by:EC | MAJORISEC| MAJORISAuthors: Emilie Chouzenoux; Jean-Baptiste Fest;Emilie Chouzenoux; Jean-Baptiste Fest;International audience; We consider the minimization of a differentiable Lipschitz gradient but non necessarily convex, function F defined on R N. We propose an accelerated gradient descent approach which combines three strategies, namely (i) a variable metric derived from the majorization-minimization principle ; (ii) a subspace strategy incorporating information from the past iterates ; (iii) a block alternating update. Under the assumption that F satisfies the Kurdyka-Łojasiewicz property, we give conditions under which the sequence generated by the resulting block majorize-minimize subspace algorithm converges to a critical point of the objective function, and we exhibit convergence rates for its iterates.
Hyper Article en Lig... arrow_drop_down Optimization LettersArticle . 2023 . Peer-reviewedLicense: Springer Nature TDMData sources: CrossrefHAL DescartesReport . 2022Full-Text: https://hal.science/hal-03920026v1/documentData sources: HAL DescartesHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s11590-023-02055-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down Optimization LettersArticle . 2023 . Peer-reviewedLicense: Springer Nature TDMData sources: CrossrefHAL DescartesReport . 2022Full-Text: https://hal.science/hal-03920026v1/documentData sources: HAL DescartesHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s11590-023-02055-z&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Preprint , Report , Article , Other literature type 2024 SwedenPublisher:Elsevier BV Funded by:UKRI | UAS Authentication Servic..., ANR | PGSEUKRI| UAS Authentication Service (UASAS) ,ANR| PGSEAuthors: Grenet, Julien; Grönqvist, Hans; Niknami, Susan;Grenet, Julien; Grönqvist, Hans; Niknami, Susan;Electronic monitoring (EM) has emerged as a popular tool for curbing the growth of large prison populations. Evidence on the causal effects of EM on criminal recidivism is, however, limited and it is unclear how this alternative to incarceration affects the labor supply of offenders and the outcomes of their family members. We study the country wide expansion of EM in Sweden in 1997 where in offenders sentenced to up to three months in prison were granted the option to substitute incarceration with EM. Our difference-in-differences estimates, which compare the change in the prison inflow rate of treated offenders to that of non-treated offenders with slightly longer sentences, show that the reform significantly decreased the number of incarcerations. Our main finding is that EM not only lowers criminal recidivism but also increases labor supply. Additionally, EM improves the educational attainment and early-life earnings of the children whose parents were exposed to the reform. The primary mechanisms through which EM operates appear to involve the preservation of offenders’ ties to the labor market, by reducing the barriers to both finding a job and changing employers. Our calculations suggest that the social benefits stemming from EM are about seven times larger than the fiscal savings associated with reduced prison expenditures, implying that the welfare gains from EM could be much greater than previously acknowledged.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jpubeco.2023.105051&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jpubeco.2023.105051&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Report , Other literature type 2023 FrancePublisher:Zenodo Authors: Raevskikh, Elena; Khalid, Usman; Pinto, Jorge;Raevskikh, Elena; Khalid, Usman; Pinto, Jorge;This report is the first statistical overview of the share of the culture sector in Abu Dhabi’s GDP (Gross Domestic Product). The analysis is based on the Statistics Centre Abu Dhabi (SCAD) Annual Economic Survey data available for the 2005–20 period. The approach to the data analysis has been harmonised through a leading international benchmark in culture statistics, the Eurostat ESS-Net Culture framework.
add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert add ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404260&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Report 2023 FrancePublisher:Zenodo Authors: Raevskikh, Elena; Pinto, Jorge; Khalid, Usman;Raevskikh, Elena; Pinto, Jorge; Khalid, Usman;This report is the first statistical overview of the exports and imports of cultural goods in Abu Dhabi. The analysis is based on Statistics Centre Abu Dhabi (SCAD) data available for the 2014– 20 period and data from Abu Dhabi Chamber of Commerce and Industry (ADCCI) Certificates of Origin (2020). The approach to the data analysis has been harmonised with a leading international benchmark in culture statistics — the Eurostat ESS-Net Culture framework.
ZENODO arrow_drop_down Hyper Article en Ligne; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Report . 2021License: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404232&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert ZENODO arrow_drop_down Hyper Article en Ligne; HAL AMU; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Report . 2021License: CC BY NCadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.5281/zenodo.10404232&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Conference object , Preprint , Report , Other literature type 2023 France, GermanyPublisher:Society for Industrial & Applied Mathematics (SIAM) Funded by:EC | SYSTEMATICGRAPH, ANR | DISTANCIAEC| SYSTEMATICGRAPH ,ANR| DISTANCIAJérémie Chalopin; Victor Chepoi; Fionn Mc Inerney; Sébastien Ratel; Yann Vaxès;One of the open problems in machine learning is whether any set-family of VC-dimension $d$ admits a sample compression scheme of size~$O(d)$. In this paper, we study this problem for balls in graphs. For balls of arbitrary radius $r$, we design proper sample compression schemes of size $2$ for trees, of size $3$ for cycles, of size $4$ for interval graphs, of size $6$ for trees of cycles, and of size $22$ for cube-free median graphs. For balls of a given radius, we design proper labeled sample compression schemes of size $2$ for trees and of size $4$ for interval graphs. We also design approximate sample compression schemes of size 2 for balls of $\delta$-hyperbolic graphs. Comment: 26 pages, 9 figures
arXiv.org e-Print Ar... arrow_drop_down Dagstuhl Research Online Publication ServerOther literature type . 2022License: CC BYData sources: Dagstuhl Research Online Publication ServerHAL AMU; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2022License: CC BYFull-Text: https://hal.science/hal-03854487/documenthttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1137/22m1527817&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen bronze 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down Dagstuhl Research Online Publication ServerOther literature type . 2022License: CC BYData sources: Dagstuhl Research Online Publication ServerHAL AMU; Mémoires en Sciences de l'Information et de la CommunicationConference object . 2022License: CC BYFull-Text: https://hal.science/hal-03854487/documenthttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1137/22m1527817&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Report , Other literature type , Preprint 2023 FrancePublisher:Elsevier BV Funded by:EC | MAJORISEC| MAJORISAuthors: Yunshi Huang; Emilie Chouzenoux; Víctor Elvira; Jean-Christophe Pesquet;Yunshi Huang; Emilie Chouzenoux; Víctor Elvira; Jean-Christophe Pesquet;International audience; Bayesian neural networks (BNNs) have received an increased interest in the last years. In BNNs, a complete posterior distribution of the unknown weight and bias parameters of the network is produced during the training stage. This probabilistic estimation offers several advantages with respect to point-wise estimates, in particular, the ability to provide uncertainty quantification when predicting new data. This feature inherent to the Bayesian paradigm, is useful in countless machine learning applications. It is particularly appealing in areas where decision-making has a crucial impact, such as medical healthcare or autonomous driving. The main challenge of BNNs is the computational cost of the training procedure since Bayesian techniques often face a severe curse of dimensionality. Adaptive importance sampling (AIS) is one of the most prominent Monte Carlo methodologies benefiting from sounded convergence guarantees and ease for adaptation. This work aims to show that AIS constitutes a successful approach for designing BNNs. More precisely, we propose a novel algorithm named PMCnet that includes an efficient adaptation mechanism, exploiting geometric information on the complex (often multimodal) posterior distribution. Numerical results illustrate the excellent performance and the improved exploration capabilities of the proposed method for both shallow and deep neural networks.
Hyper Article en Lig... arrow_drop_down Journal of the Franklin InstituteArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jfranklin.2023.08.044&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down Journal of the Franklin InstituteArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.jfranklin.2023.08.044&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Report , Preprint 2023 ItalyPublisher:Elsevier BV Funded by:UKRI | Enabling rapid adoption o..., EC | MINOAUKRI| Enabling rapid adoption of artificial intelligence through an anonymized data protocol and explainable models ,EC| MINOAAuthors: Renan Spencer Trindade; Claudia D'Ambrosio; Antonio Frangioni; Claudio Gentile;Renan Spencer Trindade; Claudia D'Ambrosio; Antonio Frangioni; Claudio Gentile;handle: 11568/1212787
Our study is motivated by the solution of Mixed-Integer Non-Linear Programming (MINLP) problems with separable non-convex functions via the Sequential Convex MINLP technique, an iterative method whose main characteristic is that of solving, for bounding purposes, piecewise-convex MINLP relaxations obtained by identifying the intervals in which each univariate function is convex or concave and then relaxing the concave parts with piecewise-linear relaxations of increasing precision. This process requires the introduction of new binary variables for the activation of the intervals where the functions are defined. In this paper we compare the three different standard formulations for the lower bounding subproblems and we show, both theoretically and computationally, that -- unlike in the piecewise-linear case -- they are not equivalent when the perspective reformulation is applied to reinforce the formulation in the segments where the original functions are convex.
arXiv.org e-Print Ar... arrow_drop_down Operations Research LettersArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Article . 2022 . 2023Archivio della Ricerca - Università di PisaArticle . 2023Data sources: Archivio della Ricerca - Università di Pisahttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.orl.2023.11.003&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert arXiv.org e-Print Ar... arrow_drop_down Operations Research LettersArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: CrossrefHyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Article . 2022 . 2023Archivio della Ricerca - Università di PisaArticle . 2023Data sources: Archivio della Ricerca - Università di Pisahttps://doi.org/10.48550/arxiv...Article . 2022License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.orl.2023.11.003&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Report , Other literature type 2023 FrancePublisher:IEEE Minh, Céline; Vermeulen, Kevin; Lefebvre, Cédric; Owezarski, Philippe; Ritchie, William;International audience; Machine learning (ML) is a promising technology for network intrusion detection systems. There is a wide range of ML algorithms that are potential candidates for network intrusion detection systems, as they exhibit very good detection accuracy in average. However, significant detection differences appear when facing different kinds of attacks, some being prone to better detect some particular attack types. They then often appear to complement each other. The challenge then lies in determining the accurate result when several ML models provide different results, and this without any explanation about their decision. To address this challenge, our system aims to reconstruct attack patterns from the outputs of these ML models and presenting them in an interpretable manner. For that, we propose an approach combining ensemble learning and stacking with a meta-learner that works on graphical representation of traffic flows, that then provides the required explainability level for the decisions made. The evaluation of our system, using the CSE-CIC-IDS2018 dataset, demonstrates a significant improvement achieved through the combination of multiple ML algorithms. Furthermore, we emphasize the importance of explainability in network intrusion detection systems and the need for accurate and interpretable models. Our system goes beyond traditional detection methods by reporting anomalous feature pairs and providing visual representations of attack patterns, empowering analysts to better understand and respond to network threats.
Hyper Article en Lig... arrow_drop_down https://doi.org/10.23919/cnsm5...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: CrossrefMémoires en Sciences de l'Information et de la Communication; HAL-INSA ToulouseConference object . 2023Full-Text: https://hal.science/hal-04228893/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23919/cnsm59352.2023.10327818&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down https://doi.org/10.23919/cnsm5...Conference object . 2023 . Peer-reviewedLicense: STM Policy #29Data sources: CrossrefMémoires en Sciences de l'Information et de la Communication; HAL-INSA ToulouseConference object . 2023Full-Text: https://hal.science/hal-04228893/documentadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.23919/cnsm59352.2023.10327818&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Preprint , Article , Report , Other literature type 2023 Belgium, FrancePublisher:Springer Science and Business Media LLC Robert John Kolesar; Guido Erreygers; Wim Van Damme; Vanara Chea; Theany Choeurng; Soklong Leng;pmid: 37805483
pmc: PMC10559627
Abstract Background Financial risk protection is a core dimension of universal health coverage. Hardship financing, defined as borrowing and selling land or assets to pay for healthcare, is a measure of last recourse. Increasing indebtedness and high interest rates, particularly among unregulated money lenders, can lead to a vicious cycle of poverty and exacerbate inequity. Methods To inform efforts to improve Cambodia’s social health protection system we analyze 2019–2020 Cambodia Socio-economic Survey data to assess hardship financing, illness and injury related productivity loss, and estimate related economic impacts. We apply two-stage Instrumental Variable multiple regression to address endogeneity relating to net income. In addition, we calculate a direct economic measure to facilitate the regular monitoring and reporting on the devastating burden of excessive out-of-pocket expenditure for policy makers. Results More than 98,500 households or 2.7% of the total population resorted to hardship financing over the past year. Factors significantly increasing risk are higher out-of-pocket healthcare expenditures, illness or injury related productivity loss, and spending of savings. The economic burden from annual lost productivity from illness or injury amounts to US$ 459.9 million or 1.7% of GDP. The estimated household economic cost related to hardship financing is US$ 250.8 million or 0.9% of GDP. Conclusions Such losses can be mitigated with policy measures such as linking a catastrophic health coverage mechanism to the Health Equity Funds, capping interest rates on health-related loans, and using loan guarantees to incentivize microfinance institutions and banks to refinance health-related, high-interest loans from money lenders. These measures could strengthen social health protection by enhancing financial risk protection, mitigating vulnerability to the devastating economic effects of health shocks, and reducing inequities.
International Journa... arrow_drop_down Institutional Repository Universiteit AntwerpenReport . 2021Data sources: Institutional Repository Universiteit AntwerpenInstitutional Repository Universiteit AntwerpenArticle . 2023Data sources: Institutional Repository Universiteit AntwerpenInternational Journal for Equity in HealthArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12939-023-02016-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen gold 0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert International Journa... arrow_drop_down Institutional Repository Universiteit AntwerpenReport . 2021Data sources: Institutional Repository Universiteit AntwerpenInstitutional Repository Universiteit AntwerpenArticle . 2023Data sources: Institutional Repository Universiteit AntwerpenInternational Journal for Equity in HealthArticle . 2023 . Peer-reviewedLicense: CC BYData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1186/s12939-023-02016-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article 2023 FrancePublisher:Elsevier BV Authors: Pooja Gupta; Angshul Majumdar; Emilie Chouzenoux; Giovanni Chierchia;Pooja Gupta; Angshul Majumdar; Emilie Chouzenoux; Giovanni Chierchia;International audience; In Drug-Drug-Interaction (DDI), the task is to predict the (adverse) effect of administering two drugs simultaneously. Currently, the techniques proposed in this direction are generally based on either shallow learning paradigms like Random Decision Forest (RDF), Logistic Regression (LR), Support Vector Machines (SVM), etc., or deep Convolutional Neural Networks (CNNs). However, specific works combine traditional machine learning (ML) algorithms such as RDF, LR, SVM, and deep learning paradigms such as CNNs in a piecemeal fashion which might not be optimal. Hence, the present work proposes a framework that presents a joint end-to-end solution. We propose a Siamese-like architecture with two processing channels' networks based on deep convolutional transform learning. Common fused representations as well as channel-wise representations are learnt, in addition with the transform across them. The final representation is passed to a decision forest to give final predictions. The proposed method is thus a supervised end-to-end multi-channel fusion framework that (i) learns unique and interpretable filters in contrast with CNNs, and (ii) jointly learns and optimizes decision forest in contrast with state-of-the-art piecemeal approach. We apply this technique to identify DDIs among 1059 drugs from the DrugBank database showing superiority of our method compared to the state-of-the-art(s).
INRIA a CCSD electro... arrow_drop_down INRIA a CCSD electronic archive server; Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationReport . Other literature type . 2022Full-Text: https://hal.science/hal-03897934/documentExpert Systems with ApplicationsArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.eswa.2023.120238&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu2 citations 2 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert INRIA a CCSD electro... arrow_drop_down INRIA a CCSD electronic archive server; Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationReport . Other literature type . 2022Full-Text: https://hal.science/hal-03897934/documentExpert Systems with ApplicationsArticle . 2023 . Peer-reviewedLicense: Elsevier TDMData sources: Crossrefadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1016/j.eswa.2023.120238&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Article , Report , Other literature type 2023 FrancePublisher:Springer Science and Business Media LLC Funded by:EC | MAJORISEC| MAJORISAuthors: Emilie Chouzenoux; Jean-Baptiste Fest;Emilie Chouzenoux; Jean-Baptiste Fest;International audience; We consider the minimization of a differentiable Lipschitz gradient but non necessarily convex, function F defined on R N. We propose an accelerated gradient descent approach which combines three strategies, namely (i) a variable metric derived from the majorization-minimization principle ; (ii) a subspace strategy incorporating information from the past iterates ; (iii) a block alternating update. Under the assumption that F satisfies the Kurdyka-Łojasiewicz property, we give conditions under which the sequence generated by the resulting block majorize-minimize subspace algorithm converges to a critical point of the objective function, and we exhibit convergence rates for its iterates.
Hyper Article en Lig... arrow_drop_down Optimization LettersArticle . 2023 . Peer-reviewedLicense: Springer Nature TDMData sources: CrossrefHAL DescartesReport . 2022Full-Text: https://hal.science/hal-03920026v1/documentData sources: HAL DescartesHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s11590-023-02055-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu0 citations 0 popularity Average influence Average impulse Average Powered by BIP!more_vert Hyper Article en Lig... arrow_drop_down Optimization LettersArticle . 2023 . Peer-reviewedLicense: Springer Nature TDMData sources: CrossrefHAL DescartesReport . 2022Full-Text: https://hal.science/hal-03920026v1/documentData sources: HAL DescartesHAL Descartes; INRIA a CCSD electronic archive server; Mémoires en Sciences de l'Information et de la CommunicationArticle . 2023License: CC BYadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.1007/s11590-023-02055-z&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu