Kleomenis Katevas

Orcid: 0000-0002-2945-5434

According to our database1, Kleomenis Katevas authored at least 34 papers between 2014 and 2024.

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Bibliography

2024
Context-Aware Membership Inference Attacks against Pre-trained Large Language Models.
CoRR, 2024

MELTing point: Mobile Evaluation of Language Transformers.
CoRR, 2024

2023
P4L: Privacy Preserving Peer-to-Peer Learning for Infrastructureless Setups.
CoRR, 2023

2022
A PIMS Development Kit for New Personal Data Platforms.
IEEE Internet Comput., 2022

BatteryLab: A Collaborative Platform for Power Monitoring.
CoRR, 2022

Privacy-preserving AI for future networks.
Commun. ACM, 2022

Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning.
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.
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.
Proceedings of the Passive and Active Measurement - 23rd International Conference, 2022

FLaaS - enabling practical federated learning on mobile environments.
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.
GetMobile Mob. Comput. Commun., 2021

PPFL: privacy-preserving federated learning with trusted execution environments.
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.
IEEE Trans. Knowl. Data Eng., 2020

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics.
IEEE Internet Things J., 2020

Decentralized Policy-Based Private Analytics.
CoRR, 2020

DarkneTZ: towards model privacy at the edge using trusted execution environments.
Proceedings of the MobiSys '20: The 18th Annual International Conference on Mobile Systems, 2020

FLaaS: Federated Learning as a Service.
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.
CoRR, 2019

BatteryLab, a distributed power monitoring platform for mobile devices: demo abstract.
Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 2019

Finding Dory in the Crowd: Detecting Social Interactions using Multi-Modal Mobile Sensing.
Proceedings of the 1st Workshop on Machine Learning on Edge in Sensor Systems, 2019

BatteryLab, A Distributed Power Monitoring Platform For Mobile Devices.
Proceedings of the 18th ACM Workshop on Hot Topics in Networks, 2019

Poster: Towards Characterizing and Limiting Information Exposure in DNN Layers.
Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications Security, 2019

2018
Analysing crowd behaviours using mobile sensing.
PhD thesis, 2018

The potential of wearable technology for monitoring social interactions based on interpersonal synchrony.
Proceedings of the 4th ACM Workshop on Wearable Systems and Applications, 2018

Typical phone use habits: intense use does not predict negative well-being.
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.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017

Continual Prediction of Notification Attendance with Classical and Deep Network Approaches.
CoRR, 2017

Privacy-Preserving Deep Inference for Rich User Data on The Cloud.
CoRR, 2017

Demo: Detecting Group Formations using iBeacon Technology.
Proceedings of the 15th Annual International Conference on Mobile Systems, 2017

Practical Processing of Mobile Sensor Data for Continual Deep Learning Predictions.
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.
Proceedings of the 12th International Conference on Intelligent Environments, 2016

Detecting group formations using iBeacon technology.
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.
Proceedings of the 2nd workshop on Workshop on Physical Analytics, 2015

2014
Poster: SensingKit: a multi-platform mobile sensing framework for large-scale experiments.
Proceedings of the 20th Annual International Conference on Mobile Computing and Networking, 2014


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