Publications associées à Mobile internet device

Deplatforming did not decrease Parler users' activity on fringe social media

Online platforms have banned ("deplatformed") influencers, communities, and even entire websites to reduce content deemed harmful. Deplatformed users often migrate to alternative platforms, which raises concerns about the effectiveness of deplatforming. He ...

OXFORD UNIV PRESS2023

Space allocation for multi-modal urban networks with ridesplitting services and public transport

Nikolaos Geroliminis, Lynn Fayed

The surge of Mobility on Demand (MoD) is largely attributed to advancements in mobile internet and technology. Ridesourcing platforms, among other solution services, offer convenience and flexibility when it comes to pick-up/drop-off time and location, all ...

The National Academies of Sciences, Engineering, and Medicine2022

Advances and Open Problems in Federated Learning

Martin Jaggi, Sebastian Urban Stich, Lie He, Yang Liu, Ayfer Özgür Aydin, Florian Tramèr, Qiang Yang, Ananda Theertha Suresh, Badih Ghazi

Federated learning (FL) is a machine learning setting where many clients (e.g., mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g., service provider), while keeping the training data decen ...

NOW PUBLISHERS INC2021

DOMAIN ADAPTATION FOR GENERALIZATION OF FACE PRESENTATION ATTACK DETECTION IN MOBILE SETTINGS WITH MINIMAL INFORMATION

Sébastien Marcel, Amir Mohammadi

With face-recognition (FR) increasingly replacing fingerprint sensors for user-authentication on mobile devices, presentation attacks (PA) have emerged as the single most significant hurdle for manufacturers of FR systems. Current machine-learning based pr ...

IEEE2020

FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction

Rachid Guerraoui, Anne-Marie Kermarrec, Rhicheek Patra, Georgios Damaskinos, Vlad-Tiberiu Nitu

Federated Learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users local. Standard FL infrastructures are however designed to have no energy or ...

Association for Computing Machinery2020

Mneme: A Mobile Distributed Ledger

Boi Faltings, Sujit Prakash Gujar, Dimitrios Chatzopoulos

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on device-to-device (D2D) ecosystems (e.g., crowdsensing). More sophisticated applications, like cryptocurrencies, need ...

IEEE2020

Instruction, Student Engagement and Learning Outcomes: A Case Study Using Anonymous Social Media in a Face-to-face Classroom

Denis Gillet, Maria Jesus Rodriguez Triana, Adrian Christian Holzer

With the wide availability of mobile devices and the growing interest in social media, numerous applications have emerged to support student engagement in the classroom. There is conflicting evidence, however, on whether the engagement benefits of such app ...

2020

IMPROVING CROSS-DATASET PERFORMANCE OF FACE PRESENTATION ATTACK DETECTION SYSTEMS USING FACE RECOGNITION DATASETS

Sébastien Marcel, Amir Mohammadi

Presentation attack detection (PAD) is now considered critically important for any face-recognition (FR) based access-control system. Current deep-learning based PAD systems show excellent performance when they are tested in intra-dataset scenarios. Under ...

IEEE2020

L'importance croissante de la qualité des temps de déplacements

Vincent Kaufmann, Emmanuel Pierre Jean Ravalet, Guillaume Simon Joseph Drevon, Yann Francis Eric Dubois

Bien que la constance du Budget-Temps de Transport (BTT) a longtemps prévalu (Zahavi et Talvitie 1980), des travaux récents indiquent une augmentation substantielle du BTT. En effet, les personnes semblent en moyenne, consacrer de plus en plus de temps à l ...

MetisPresses2019

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Mobile internet device

Deplatforming did not decrease Parler users' activity on fringe social media

Groove: Flexible Metadata-Private Messaging

Space allocation for multi-modal urban networks with ridesplitting services and public transport

Advances and Open Problems in Federated Learning

DOMAIN ADAPTATION FOR GENERALIZATION OF FACE PRESENTATION ATTACK DETECTION IN MOBILE SETTINGS WITH MINIMAL INFORMATION

FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction

Mneme: A Mobile Distributed Ledger

Instruction, Student Engagement and Learning Outcomes: A Case Study Using Anonymous Social Media in a Face-to-face Classroom

IMPROVING CROSS-DATASET PERFORMANCE OF FACE PRESENTATION ATTACK DETECTION SYSTEMS USING FACE RECOGNITION DATASETS

L'importance croissante de la qualité des temps de déplacements

Graph Chatbot

Chattez avec Graph Search

Groove: Flexible Metadata-Private Messaging

IMPROVING CROSS-DATASET PERFORMANCE OF FACE PRESENTATION ATTACK DETECTION SYSTEMS USING FACE RECOGNITION DATASETS

DOMAIN ADAPTATION FOR GENERALIZATION OF FACE PRESENTATION ATTACK DETECTION IN MOBILE SETTINGS WITH MINIMAL INFORMATION

Space allocation for multi-modal urban networks with ridesplitting services and public transport

Instruction, Student Engagement and Learning Outcomes: A Case Study Using Anonymous Social Media in a Face-to-face Classroom

Deplatforming did not decrease Parler users' activity on fringe social media

L'importance croissante de la qualité des temps de déplacements

FLeet: Online Federated Learning via Staleness Awareness and Performance Prediction

Mneme: A Mobile Distributed Ledger

Advances and Open Problems in Federated Learning