Kleomenis Katevas

According to our database, Kleomenis Katevas authored at least 33 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

MELTing point: Mobile Evaluation of Language Transformers.

Stefanos Laskaridis, Kleomenis Katevas, Lorenzo Minto, Hamed Haddadi

CoRR, 2024

2023

P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups.

Ioannis Arapakis, Panagiotis Papadopoulos, Kleomenis Katevas, Diego Perino

CoRR, 2023

2022

A PIMS Development Kit for New Personal Data Platforms.

Nikhil Jha, Martino Trevisan, Luca Vassio, Marco Mellia, Stefano Traverso, Álvaro García-Recuero, Nikolaos Laoutaris, Amir Mehrjoo, Santiago Andrés Azcoitia, Rubén Cuevas Rumín, Kleomenis Katevas, Panagiotis Papadopoulos, Nicolas Kourtellis, Roberto Gonzalez, Xavi Olivares, George-Marios Kalatzantonakis-Jullien

IEEE Internet Comput., 2022

BatteryLab: A Collaborative Platform for Power Monitoring.

Matteo Varvello, Kleomenis Katevas, Mihai Plesa, Hamed Haddadi, Fabián E. Bustamante, Ben Livshits

CoRR, 2022

Privacy-preserving AI for future networks.

Diego Perino, Kleomenis Katevas, Andra Lutu, Eduard Marin, Nicolas Kourtellis

Commun. ACM, 2022

Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning.

Dusan Stamenkovic, Alexandros Karatzoglou, Ioannis Arapakis, Xin Xin, Kleomenis Katevas

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

FLaaS - practical federated learning as a service for mobile applications.

Kleomenis Katevas, Diego Perino, Nicolas Kourtellis

Proceedings of the HotMobile '22: The 23rd International Workshop on Mobile Computing Systems and Applications, Tempe, Arizona, USA, March 9, 2022

BatteryLab: A Collaborative Platform for Power Monitoring - https: //batterylab.dev.

Matteo Varvello, Kleomenis Katevas, Mihai Plesa, Hamed Haddadi, Fabián E. Bustamante, Ben Livshits

Proceedings of the Passive and Active Measurement - 23rd International Conference, 2022

FLaaS - enabling practical federated learning on mobile environments.

Kleomenis Katevas, Diego Perino, Nicolas Kourtellis

Proceedings of the MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services, Portland, Oregon, 27 June 2022, 2022

2021

PPFL: Enhancing Privacy in Federated Learning with Confidential Computing.

Fan Mo, Hamed Haddadi, Kleomenis Katevas, Eduard Marin, Diego Perino, Nicolas Kourtellis

GetMobile Mob. Comput. Commun., 2021

PPFL: privacy-preserving federated learning with trusted execution environments.

Fan Mo, Hamed Haddadi, Kleomenis Katevas, Eduard Marin, Diego Perino, Nicolas Kourtellis

Proceedings of the MobiSys '21: The 19th Annual International Conference on Mobile Systems, Applications, and Services, Virtual Event, Wisconsin, USA, 24 June, 2021

2020

Deep Private-Feature Extraction.

Seyed Ali Osia, Ali Taheri, Ali Shahin Shamsabadi, Kleomenis Katevas, Hamed Haddadi, Hamid R. Rabiee

IEEE Trans. Knowl. Data Eng., 2020

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics.

Seyed Ali Osia, Ali Shahin Shamsabadi, Sina Sajadmanesh, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi

IEEE Internet Things J., 2020

Decentralized Policy-Based Private Analytics.

Kleomenis Katevas, Eugene Bagdasaryan, Jason Waterman, Mohamad Mounir Safadieh, Hamed Haddadi, Deborah Estrin

CoRR, 2020

DarkneTZ: towards model privacy at the edge using trusted execution environments.

Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Soteris Demetriou, Ilias Leontiadis, Andrea Cavallaro, Hamed Haddadi

Proceedings of the MobiSys '20: The 18th Annual International Conference on Mobile Systems, 2020

FLaaS: Federated Learning as a Service.

Nicolas Kourtellis, Kleomenis Katevas, Diego Perino

Proceedings of the DistributedML@CoNEXT 2020: Proceedings of the 1st Workshop on Distributed Machine Learning, 2020

2019

Towards Characterizing and Limiting Information Exposure in DNN Layers.

Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Andrea Cavallaro, Hamed Haddadi

CoRR, 2019

BatteryLab, a distributed power monitoring platform for mobile devices: demo abstract.

Matteo Varvello, Kleomenis Katevas, Wei Hang, Mihai Plesa, Hamed Haddadi, Fabián E. Bustamante, Benjamin Livshits

Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 2019

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

Kleomenis Katevas, Katrin Hänsel, Richard G. Clegg, Ilias Leontiadis, Hamed Haddadi, Laurissa N. Tokarchuk

Proceedings of the 1st Workshop on Machine Learning on Edge in Sensor Systems, 2019

BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices.

Matteo Varvello, Kleomenis Katevas, Mihai Plesa, Hamed Haddadi, Benjamin Livshits

Proceedings of the 18th ACM Workshop on Hot Topics in Networks, 2019

Poster: Towards Characterizing and Limiting Information Exposure in DNN Layers.

Fan Mo, Ali Shahin Shamsabadi, Kleomenis Katevas, Andrea Cavallaro, Hamed Haddadi

Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

2018

Analysing crowd behaviours using mobile sensing.

Kleomenis Katevas

PhD thesis, 2018

The potential of wearable technology for monitoring social interactions based on interpersonal synchrony.

Katrin Hänsel, Kleomenis Katevas, Guido Orgs, Daniel C. Richardson, Akram Alomainy, Hamed Haddadi

Proceedings of the 4th ACM Workshop on Wearable Systems and Applications, 2018

Typical phone use habits: intense use does not predict negative well-being.

Kleomenis Katevas, Ioannis Arapakis, Martin Pielot

Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services, 2018

2017

Beyond Interruptibility: Predicting Opportune Moments to Engage Mobile Phone Users.

Martin Pielot, Bruno Cardoso, Kleomenis Katevas, Joan Serrà, Aleksandar Matic, Nuria Oliver

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017

Continual Prediction of Notification Attendance with Classical and Deep Network Approaches.

Kleomenis Katevas, Ilias Leontiadis, Martin Pielot, Joan Serrà

CoRR, 2017

Privacy-Preserving Deep Inference for Rich User Data on The Cloud.

Seyed Ali Ossia, Ali Shahin Shamsabadi, Ali Taheri, Kleomenis Katevas, Hamid R. Rabiee, Nicholas D. Lane, Hamed Haddadi

CoRR, 2017

Demo: Detecting Group Formations using iBeacon Technology.

Kleomenis Katevas, Laurissa N. Tokarchuk, Hamed Haddadi, Richard G. Clegg, Muhammad Irfan

Proceedings of the 15th Annual International Conference on Mobile Systems, 2017

Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions.

Kleomenis Katevas, Ilias Leontiadis, Martin Pielot, Joan Serrà

Proceedings of the 1st International Workshop on Embedded and Mobile Deep Learning (Deep Learning for Mobile Systems and Applications), 2017

2016

SensingKit: Evaluating the Sensor Power Consumption in iOS Devices.

Kleomenis Katevas, Hamed Haddadi, Laurissa N. Tokarchuk

Proceedings of the 12th International Conference on Intelligent Environments, 2016

Detecting group formations using iBeacon technology.

Kleomenis Katevas, Hamed Haddadi, Laurissa N. Tokarchuk, Richard G. Clegg

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2016 ACM International Symposium on Wearable Computers, 2016

2015

Walking in Sync: Two is Company, Three's a Crowd.

Kleomenis Katevas, Hamed Haddadi, Laurissa N. Tokarchuk, Richard G. Clegg

Proceedings of the 2nd workshop on Workshop on Physical Analytics, 2015

2014

Poster: SensingKit: a multi-platform mobile sensing framework for large-scale experiments.

Kleomenis Katevas, Hamed Haddadi, Laurissa N. Tokarchuk

Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, 2014