Stefanos Laskaridis

According to our database, Stefanos Laskaridis authored at least 22 papers between 2019 and 2025.

Collaborative distances:

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

2025

LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning.

Nurbek Tastan, Stefanos Laskaridis, Martin Takác, Karthik Nandakumar, Samuel Horváth

CoRR, May, 2025

NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation.

Rob Romijnders, Stefanos Laskaridis, Ali Shahin Shamsabadi, Hamed Haddadi

CoRR, April, 2025

2024

The Future of Consumer Edge-AI Computing.

Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane

IEEE Pervasive Comput., 2024

A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024.

Dimitris Spathis, Aaqib Saeed, Ali Etemad, Sana Tonekaboni, Stefanos Laskaridis, Shohreh Deldari, Chi Ian Tang, Patrick Schwab, Shyam A. Tailor

CoRR, 2024

MELTing Point: Mobile Evaluation of Language Transformers.

Stefanos Laskaridis, Kleomenis Katevas, Lorenzo Minto, Hamed Haddadi

Proceedings of the 30th Annual International Conference on Mobile Computing and Networking, 2024

Recurrent Early Exits for Federated Learning with Heterogeneous Clients.

Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas Donald Lane

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition.

Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022

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

Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane

ACM Trans. Embed. Comput. Syst., November, 2022

Federated Learning for Inference at Anytime and Anywhere.

Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales

CoRR, 2022

Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs.

Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane

CoRR, 2022

FedorAS: Federated Architecture Search under system heterogeneity.

Lukasz Dudziak, Stefanos Laskaridis, Javier Fernández-Marqués

CoRR, 2022

Adaptable mobile vision systems through multi-exit neural networks.

Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane

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

Multi-Exit Semantic Segmentation Networks.

Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

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

Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane

Proceedings of the HotMobile '21: The 22nd International Workshop on Mobile Computing Systems and Applications, 2021

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

Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions.

Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane

Proceedings of the EMDL@MobiSys 2021: Proceedings of the 5th International Workshop on Embedded and Mobile Deep Learning, 2021

Federated mobile sensing for activity recognition.

Stefanos Laskaridis, Dimitris Spathis, Mário Almeida

Proceedings of the ACM MobiCom '21: The 27th Annual International Conference on Mobile Computing and Networking, 2021

Smart at what cost?: characterising mobile deep neural networks in the wild.

Mário Almeida, Stefanos Laskaridis, Abhinav Mehrotra, Lukasz Dudziak, Ilias Leontiadis, Nicholas D. Lane

Proceedings of the IMC '21: ACM Internet Measurement Conference, 2021

2020

SPINN: synergistic progressive inference of neural networks over device and cloud.

Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane

Proceedings of the MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking, 2020

HAPI: Hardware-Aware Progressive Inference.

Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2020

2019

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

Mário Almeida, Stefanos Laskaridis, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane

CoRR, 2019

ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning.

Lukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla, Stefanos Laskaridis, Nicholas D. Lane

Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019