Ilias Leontiadis

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Senior Researcher- Mobile Systems, Networks, Machine Learning at Telefónica Research, Researcher at Telefónica Research from 2013-2017, Research Associate at University of Cambridge from 2009-2013, PhD Graduate at University College London from 2006-2009, Research Intern at Microsoft Research Cambridge from 2008-2009

Featured Co-authors

Gianluca Stringhini
41 publications
Hamed Haddadi
40 publications
Nicholas D. Lane
39 publications
Emiliano De Cristofaro
38 publications
Jeremy Blackburn
34 publications
Nicolas Kourtellis
31 publications
Andrea Cavallaro
30 publications
Joan Serrà
29 publications
Savvas Zannettou
28 publications
Stylianos I. Venieris
24 publications
Ali Shahin Shamsabadi
13 publications

How to Reach Real-Time AI on Consumer Devices? Solutions for Programmable and Custom Architectures

The unprecedented performance of deep neural networks (DNNs) has led to ...
06/21/2021 ∙ by Stylianos I. Venieris, et al. ∙ 0 ∙ share

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DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device

Recently, there has been an explosive growth of mobile and embedded appl...
04/20/2021 ∙ by Mario Almeida, et al. ∙ 0 ∙ share

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FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout

Federated Learning (FL) has been gaining significant traction across dif...
02/26/2021 ∙ by Samuel Horvath, et al. ∙ 0 ∙ share

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It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation

On-device machine learning is becoming a reality thanks to the availabil...
02/02/2021 ∙ by Ilias Leontiadis, et al. ∙ 0 ∙ share

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SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud

Despite the soaring use of convolutional neural networks (CNNs) in mobil...
08/14/2020 ∙ by Stefanos Laskaridis, et al. ∙ 9 ∙ share

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A Retrospective Analysis of User Exposure to (Illicit) Cryptocurrency Mining on the Web

In late 2017, a sudden proliferation of malicious JavaScript was reporte...
04/28/2020 ∙ by Ralph Holz, et al. ∙ 0 ∙ share

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DarkneTZ: Towards Model Privacy at the Edge using Trusted Execution Environments

We present DarkneTZ, a framework that uses an edge device's Trusted Exec...
04/12/2020 ∙ by Fan Mo, et al. ∙ 20 ∙ share

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Detecting Cyberbullying and Cyberaggression in Social Media

Cyberbullying and cyberaggression are increasingly worrisome phenomena a...
07/20/2019 ∙ by Despoina Chatzakou, et al. ∙ 0 ∙ share

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EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices

In recent years, advances in deep learning have resulted in unprecedente...
05/17/2019 ∙ by Mario Almeida, et al. ∙ 5 ∙ share

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A Self-Attentive Emotion Recognition Network

Modern deep learning approaches have achieved groundbreaking performance...
04/24/2019 ∙ by Harris Partaourides, et al. ∙ 0 ∙ share

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Disturbed YouTube for Kids: Characterizing and Detecting Disturbing Content on YouTube

A considerable number of the most-subscribed YouTube channels feature co...
01/21/2019 ∙ by Kostantinos Papadamou, et al. ∙ 0 ∙ share

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LOBO -- Evaluation of Generalization Deficiencies in Twitter Bot Classifiers

Botnets in online social networks are increasingly often affecting the r...
09/25/2018 ∙ by Juan Echeverría, et al. ∙ 0 ∙ share

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Finding Dory in the Crowd: Detecting Social Interactions using Multi-Modal Mobile Sensing

Remembering our day-to-day social interactions is challenging even if yo...
08/30/2018 ∙ by Kleomenis Katevas, et al. ∙ 0 ∙ share

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There goes Wally: Anonymously sharing your location gives you away

With current technology, a number of entities have access to user mobili...
06/07/2018 ∙ by Apostolos Pyrgelis, et al. ∙ 0 ∙ share

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"You Know What to Do": Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks

Over the years, the Web has shrunk the world, allowing individuals to sh...
05/21/2018 ∙ by Enrico Mariconti, et al. ∙ 0 ∙ share

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A Unified Deep Learning Architecture for Abuse Detection

Hate speech, offensive language, sexism, racism and other types of abusi...
02/01/2018 ∙ by Antigoni-Maria Founta, et al. ∙ 0 ∙ share

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Continual Prediction of Notification Attendance with Classical and Deep Network Approaches

We investigate to what extent mobile use patterns can predict -- at the ...
12/19/2017 ∙ by Kleomenis Katevas, et al. ∙ 0 ∙ share

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