Search Results - "Arcolezi, Héber H."

On the impact of multi-dimensional local differential privacy on fairness by Makhlouf, Karima, Arcolezi, Héber H., Zhioua, Sami, Brahim, Ghassen Ben, Palamidessi, Catuscia

“…Automated decision systems are increasingly used to make consequential decisions in people’s lives. Due to the sensitivity of the manipulated data and the…”
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Machine learning-based forecasting of firemen ambulances’ turnaround time in hospitals, considering the COVID-19 impact by Cerna, Selene, Arcolezi, Héber H., Guyeux, Christophe, Royer-Fey, Guillaume, Chevallier, Céline

“…When ambulances’ turnaround time (TT) in emergency departments is prolonged, it not only affects the victim severely but also causes unavailability of…”
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Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates by Arcolezi, Héber H., Couchot, Jean-François, Al Bouna, Bechara, Xiao, Xiaokui

“…This paper investigates the problem of collecting multidimensional data throughout time (i.e., longitudinal studies) for the fundamental task of frequency…”
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Privacy-Preserving Prediction of Victim's Mortality and Their Need for Transportation to Health Facilities by Arcolezi, Heber H., Cerna, Selene, Couchot, Jean-Francois, Guyeux, Christophe, Makhoul, Abdallah

“…Emergency medical services (EMS) provide crucial prehospital care, such as in the case of cardiac arrest, where the victim requires immediate first-aid. For…”
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Forecasting the number of firefighter interventions per region with local-differential-privacy-based data by Arcolezi, Héber H., Couchot, Jean-François, Cerna, Selene, Guyeux, Christophe, Royer, Guillaume, Bouna, Béchara Al, Xiao, Xiaokui

“…Statistical studies on the number and types of firefighter interventions by region are essential to improve service to the population. It is also a preliminary…”
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Boosting Methods for Predicting Firemen Interventions by Cerna, Selene, Guyeux, Christophe, Arcolezi, Heber H., Royer, Guillaume

“…Forecasting future incidents to the next hours is of great importance for fire brigades, which allows improving their response time to interventions, one…”
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RISE controller tuning and system identification through machine learning for human lower limb rehabilitation via neuromuscular electrical stimulation by Arcolezi, Héber H., Nunes, Willian R.B.M., de Araujo, Rafael A., Cerna, Selene, Sanches, Marcelo A.A., Teixeira, Marcelo C.M., de Carvalho, Aparecido A.

“…Neuromuscular electrical stimulation (NMES) has been effectively applied in many rehabilitation treatments of individuals with spinal cord injury (SCI). In…”
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Identifying the knee joint angular position under neuromuscular electrical stimulation via long short-term memory neural networks by Arcolezi, Héber H., Nunes, Willian R. B. M., Cerna, Selene, de Araujo, Rafael A., Sanches, Marcelo Augusto Assunção, Teixeira, Marcelo Carvalho Minhoto, de Carvalho, Aparecido Augusto

“…Purpose Recurrent neural networks (RNNs) offer a promising opportunity for identifying nonlinear systems. This paper investigates the effectiveness of the long…”
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Preserving Geo-Indistinguishability of the Emergency Scene to Predict Ambulance Response Time by Arcolezi, Héber, Cerna, Selene, Guyeux, Christophe, Couchot, Jean-François

“…Emergency medical services (EMS) provide crucial emergency assistance and ambulatory services. One key measurement of EMS’s quality of service is their…”
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Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective by Arcolezi, Héber H, Gambs, Sébastien

“…Arcolezi, H\'eber H., and S\'ebastien Gambs. "Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective." Proceedings on…”
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Production of Categorical Data Verifying Differential Privacy: Conception and Applications to Machine Learning by Arcolezi, Héber H

“…Private and public organizations regularly collect and analyze digitalized data about their associates, volunteers, clients, etc. However, because most…”
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(Local) Differential Privacy has NO Disparate Impact on Fairness by Arcolezi, Héber H, Makhlouf, Karima, Palamidessi, Catuscia

“…In recent years, Local Differential Privacy (LDP), a robust privacy-preserving methodology, has gained widespread adoption in real-world applications. With…”
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On the Utility Gain of Iterative Bayesian Update for Locally Differentially Private Mechanisms by Arcolezi, Héber H, Cerna, Selene, Palamidessi, Catuscia

“…This paper investigates the utility gain of using Iterative Bayesian Update (IBU) for private discrete distribution estimation using data obfuscated with…”
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Mobility modeling through mobile data: generating an optimized and open dataset respecting privacy by Arcolezi, Heber H., Couchot, Jean-Franeois, Baala, Oumaya, Contet, Jean-Michel, Al Bouna, Bechara, Xiao, Xiaokui

“…Modeling and understanding people's mobility at a temporal and geographical space are very strict requirements for developing better strategies of urban public…”
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On the Risks of Collecting Multidimensional Data Under Local Differential Privacy by Arcolezi, Héber H, Gambs, Sébastien, Couchot, Jean-François, Palamidessi, Catuscia

“…The private collection of multiple statistics from a population is a fundamental statistical problem. One possible approach to realize this is to rely on the…”
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Frequency Estimation of Evolving Data Under Local Differential Privacy by Arcolezi, Héber H, Pinzón, Carlos, Palamidessi, Catuscia, Gambs, Sébastien

“…Collecting and analyzing evolving longitudinal data has become a common practice. One possible approach to protect the users' privacy in this context is to use…”
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A Systematic and Formal Study of the Impact of Local Differential Privacy on Fairness: Preliminary Results by Makhlouf, Karima, Stefanovic, Tamara, Arcolezi, Heber H., Palamidessi, Catuscia

“…Machine learning (ML) algorithms rely primarily on the availability of training data, and, depending on the domain, these data may include sensitive…”
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Causal Discovery Under Local Privacy by Binkytė, Rūta, Pinzón, Carlos, Lestyán, Szilvia, Jung, Kangsoo, Arcolezi, Héber H, Palamidessi, Catuscia

“…Differential privacy is a widely adopted framework designed to safeguard the sensitive information of data providers within a data set. It is based on the…”
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Multi-Freq-LDPy: Multiple Frequency Estimation Under Local Differential Privacy in Python by Arcolezi, Héber H, Couchot, Jean-François, Gambs, Sébastien, Palamidessi, Catuscia, Zolfaghari, Majid

“…This paper introduces the multi-freq-ldpy Python package for multiple frequency estimation under Local Differential Privacy (LDP) guarantees. LDP is a gold…”
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Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates by Arcolezi, Héber H, Couchot, Jean-François, Bouna, Bechara Al, Xiao, Xiaokui

“…This paper investigates the problem of collecting multidimensional data throughout time (i.e., longitudinal studies) for the fundamental task of frequency…”
Get full text