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Julio Garrote, Ignacio Gutiérrez-Pérez and Andrés Díez-Herrero
Calibration and validation of flood risk maps at a national or a supra-national level remains a problematic aspect due to the limited information available to carry out these tasks. However, this validation is essential to define the representativeness o...
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Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Gustavo O. R. Cruz, Rodrigo M. Peixoto, Guilherme A. de Sousa Guimarães, Ewerton L. S. Oliveira, Ingrid Winkler and Erick G. Sperandio Nascimento
The majority of current approaches for bias and fairness identification or mitigation in machine learning models are applications for a particular issue that fails to account for the connection between the application context and its associated sensitive...
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Laurent Risser, Agustin Martin Picard, Lucas Hervier and Jean-Michel Loubes
The problem of algorithmic bias in machine learning has recently gained a lot of attention due to its potentially strong impact on our societies. In much the same manner, algorithmic biases can alter industrial and safety-critical machine learning applic...
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Jiquan Peng, Juan Chen and Liguo Zhang
The relative poverty statuses of female and male migrant workers are complex: (i) as a group, migrant workers are relatively better off than their rural hometown fellow residents but are deprived compared to the long-term residents of the cities to which...
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Juliana Castaneda, Assumpta Jover, Laura Calvet, Sergi Yanes, Angel A. Juan and Milagros Sainz
Are algorithms sexist? This is a question that has been frequently appearing in the mass media, and the debate has typically been far from a scientific analysis. This paper aims at answering the question using a hybrid social and technical perspective. F...
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Tony Gwyn and Kaushik Roy
Image recognition technology systems have existed in the realm of computer security since nearly the inception of electronics, and have seen vast improvements in recent years. Currently implemented facial detection systems regularly achieve accuracy rate...
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Pranita Patil and Kevin Purcell
Although deep learning has proven to be tremendously successful, the main issue is the dependency of its performance on the quality and quantity of training datasets. Since the quality of data can be affected by biases, a novel deep learning method based...
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Emanuel Marques Queiroga, Matheus Francisco Batista Machado, Virgínia Rodés Paragarino, Tiago Thompsen Primo and Cristian Cechinel
This paper describes a nationwide learning analytics initiative in Uruguay focused on the future implementation of governmental policies to mitigate student retention and dropouts in secondary education. For this, data from a total of 258,440 students we...
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Norah Alshareef, Xiaohong Yuan, Kaushik Roy and Mustafa Atay
In biometric systems, the process of identifying or verifying people using facial data must be highly accurate to ensure a high level of security and credibility. Many researchers investigated the fairness of face recognition systems and reported demogra...
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Pág. 105 - 128
Equal participation of women and men in household decision-making processes is subject to controversy. The necessary preconditions for neo-liberal globalization entrap the women of the global So...
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