Publications associées à Youth nightlife at home: towards a feminist conceptualisation of home

Artificial intelligence of things for smart cities: advanced solutions for enhancing transportation safety

In the context of smart cities, ensuring road safety is crucial due to increasing urbanization and the interconnected nature of contemporary urban environments. Leveraging innovative technologies is essential to mitigate risks and create safer communities. ...

Springernature2024

A Privacy-Preserving Querying Mechanism with High Utility for Electric Vehicles

Sayan Biswas

Electric vehicles (EVs) are becoming more popular due to environmental consciousness. The limited availability of charging stations (CSs), compared to the number of EVs on the road, has led to increased range anxiety and a higher frequency of CS queries du ...

Ieee-Inst Electrical Electronics Engineers Inc2024

The Privacy Power of Correlated Noise in Decentralized Learning

Rachid Guerraoui, Martin Jaggi, Anastasiia Koloskova, Youssef Allouah, Aymane El Firdoussi

Decentralized learning is appealing as it enables the scalable usage of large amounts of distributed data and resources (without resorting to any central entity), while promoting privacy since every user minimizes the direct exposure of their data. Yet, wi ...

PMLR2024

Differentially private multi-agent constraint optimization

Boi Faltings, Aleksei Triastcyn, Sujit Prakash Gujar, Sankarshan Damle

Distributed constraint optimization (DCOP) is a framework in which multiple agents with private constraints (or preferences) cooperate to achieve a common goal optimally. DCOPs are applicable in several multi-agent coordination/allocation problems, such as ...

Springer2024

Resistances to change in urban travel behaviors

Marc-Edouard Baptiste Grégoire Schultheiss

The social discourse surrounding the climate emergency progressively infuses the society, transforming into both micro- and macro-social injunctions to change. Yet, society - grounded in a territorial, social, and cultural contingency - appears to resist t ...

EPFL2023

Challenging the Assumptions: Rethinking Privacy, Bias, and Security in Machine Learning

Bogdan Kulynych

Predictive models based on machine learning (ML) offer a compelling promise: bringing clarity and structure to complex natural and social environments. However, the use of ML poses substantial risks related to the privacy of their training data as well as ...

EPFL2023

Bridging the gap between theoretical and practical privacy technologies for at-risk populations

Kasra Edalatnejadkhamene

With the pervasive digitalization of modern life, we benefit from efficient access to information and services. Yet, this digitalization poses severe privacy challenges, especially for special-needs individuals. Beyond being a fundamental human right, priv ...

EPFL2023

Privacy-Preserving Machine Learning on Graphs

Sina Sajadmanesh

Graph Neural Networks (GNNs) have emerged as a powerful tool for learning on graphs, demonstrating exceptional performance in various domains. However, as GNNs become increasingly popular, new challenges arise. One of the most pressing is the need to ensur ...

EPFL2023

Protecting privacy through metadata analysis

Sandra Deepthy Siby

Although encryption hides the content of communications from third parties, metadata, i.e., the information attached to the content (such as the size or timing of communication) can be a rich source of details and context. In this dissertation, we demonstr ...

EPFL2022

A Functional Perspective on Information Measures

Amedeo Roberto Esposito

Since the birth of Information Theory, researchers have defined and exploited various information measures, as well as endowed them with operational meanings. Some were born as a "solution to a problem", like Shannon's Entropy and Mutual Information. Other ...

EPFL2022

Propagation of singularities for the stochastic wave equation

Cheuk Yin Lee

We study the existence and propagation of singularities of the solution to a one-dimensional linear stochastic wave equation driven by an additive Gaussian noise that is white in time and colored in space. Our approach is based on a simultaneous law of the ...

ELSEVIER2022

Impaired cognitive flexibility and heightened urgency are associated with increased alcohol consumption in rodent models of excessive drinking

Emanuela De Falco

Alcohol use disorder (AUD) is characterized by impairments in decision-making that can exist as stable traits or transient states. Cognitive inflexibility reflects an inability to update information that guides decision-making and is thought to contribute ...

WILEY2021

Ten seconds of my nights: Exploring methods to measure brightness, loudness and attendance and their associations with alcohol use from video clips

Daniel Gatica-Perez, Skanda Muralidhar, Lakmal Buddika Meegahapola

Introduction Most evidence on associations between alcohol use behaviors and the characteristics of its social and physical context is based on self-reports from study participants and, thus, only account for their subjective impressions of the situation. ...

2021

Flying in Private Mode: Understanding and Improving the Privacy ICAO Address Program

Guillaume Michel Le Bars

Location privacy of aircraft has recently gained attention as air traffic management was modernized using novel surveillance technologies. Business aviation circles and various military and government entities voiced serious concerns about automated and ub ...

AMER INST AERONAUTICS ASTRONAUTICS2021

Understanding Eating And Drinking In Context From Crowdsourced Data

Thanh Trung Phan

With the increasing rate of urbanization, understanding food and beverage consumption, including alcohol drinking behaviour with its consequences, is relevant in such a megacity in the future. Especially, investigation of alcohol drinking is necessary for ...

EPFL2020

Understanding Heavy Drinking at Night through Smartphone Sensing and Active Human Engagement

Daniel Gatica-Perez, Skanda Muralidhar, Thanh Trung Phan

Heavy alcohol consumption can lead to many severe consequences. In this paper, we study the phenomenon of heavy drinking at night (4+ drinks for women or 5+ for men on a single evening), using a smartphone sensing dataset depicting about nightlife and drin ...

ACM2020

Shooting shots: Estimating alcoholic drink sizes in real life using event-level reports and annotations of close-up pictures

Daniel Gatica-Perez, Thanh Trung Phan

Introduction and Aims Drinks consumed in real life are diverse, in terms of beverage type, container size and alcohol by volume. To date, most ecological momentary assessment studies have assessed drinking amounts with 'standard' drinks, although their eve ...

WILEY2021

Learning Urban Nightlife Routines from Mobile Data

Daniel Gatica-Perez, Thanh Trung Phan

The use of smartphone sensing for public health studies is appealing to understand routines. We present an approach to learn nightlife routines in a smartphone sensing dataset volunteered by 184 young people (1586 weekend nights with location data captured ...

ACM2020

Data-Aware Privacy-Preserving Machine Learning

Aleksei Triastcyn

In this thesis, we focus on the problem of achieving practical privacy guarantees in machine learning (ML), where the classic differential privacy (DP) fails to maintain a good trade-off between user privacy and data utility. Differential privacy guarantee ...

EPFL2020

Privacy-Aware Digital Mediation Tools for Improving Adolescent Mental Well-being: Application to School Bullying

Denis Gillet, Isabelle Barbara Marie-Hélène Cardia, Maria Gaci

In human-computer interaction, self-disclosure of sensitive information regarding distressing experiences requires the establishment of a trust channel between the user and the digital tool. As privacy and security have been identified as factors that cont ...

2020