Ilias Leontiadis | DeepAI

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Featured Co-authors

Nicholas D. Lane
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Savvas Zannettou
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Joan Serrà
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Stylianos I. Venieris
34 publications

∙ 05/22/2023

EXACT: Extensive Attack for Split Learning

Privacy-Preserving machine learning (PPML) can help us train and deploy ...

0 Xinchi Qiu, et al. ∙

∙ 06/07/2022

FEL: High Capacity Learning for Recommendation and Ranking via Federated Ensemble Learning

Federated learning (FL) has emerged as an effective approach to address ...

0 Meisam Hejazinia, et al. ∙

∙ 09/28/2021

Smart at what cost? Characterising Mobile Deep Neural Networks in the wild

With smartphones' omnipresence in people's pockets, Machine Learning (ML...

0 Mario Almeida, et al. ∙

∙ 06/21/2021

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 ...

0 Stylianos I. Venieris, et al. ∙

∙ 04/20/2021

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

Recently, there has been an explosive growth of mobile and embedded appl...

0 Mario Almeida, et al. ∙

∙ 02/26/2021

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

Federated Learning (FL) has been gaining significant traction across dif...

0 Samuel Horvath, et al. ∙

∙ 02/02/2021

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...

0 Ilias Leontiadis, et al. ∙

∙ 08/14/2020

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

Despite the soaring use of convolutional neural networks (CNNs) in mobil...

9 Stefanos Laskaridis, et al. ∙

∙ 04/28/2020

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

In late 2017, a sudden proliferation of malicious JavaScript was reporte...

0 Ralph Holz, et al. ∙

∙ 04/12/2020

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

We present DarkneTZ, a framework that uses an edge device's Trusted Exec...

20 Fan Mo, et al. ∙

∙ 07/20/2019

Detecting Cyberbullying and Cyberaggression in Social Media

Cyberbullying and cyberaggression are increasingly worrisome phenomena a...

0 Despoina Chatzakou, et al. ∙

∙ 05/17/2019

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

In recent years, advances in deep learning have resulted in unprecedente...

5 Mario Almeida, et al. ∙

∙ 04/24/2019

A Self-Attentive Emotion Recognition Network

Modern deep learning approaches have achieved groundbreaking performance...

0 Harris Partaourides, et al. ∙

∙ 01/21/2019

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

A considerable number of the most-subscribed YouTube channels feature co...

0 Kostantinos Papadamou, et al. ∙

∙ 09/25/2018

LOBO -- Evaluation of Generalization Deficiencies in Twitter Bot Classifiers

Botnets in online social networks are increasingly often affecting the r...

0 Juan Echeverría, et al. ∙

∙ 08/30/2018

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...

0 Kleomenis Katevas, et al. ∙

∙ 06/07/2018

There goes Wally: Anonymously sharing your location gives you away

With current technology, a number of entities have access to user mobili...

0 Apostolos Pyrgelis, et al. ∙

∙ 05/21/2018

"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...

0 Enrico Mariconti, et al. ∙

∙ 02/01/2018

A Unified Deep Learning Architecture for Abuse Detection

Hate speech, offensive language, sexism, racism and other types of abusi...

0 Antigoni-Maria Founta, et al. ∙

∙ 12/19/2017

Continual Prediction of Notification Attendance with Classical and Deep Network Approaches

We investigate to what extent mobile use patterns can predict -- at the ...

0 Kleomenis Katevas, et al. ∙

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