Stefanos Laskaridis

Orcid: 0000-0002-8875-7328

According to our database1, Stefanos Laskaridis authored at least 20 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
The Future of Consumer Edge-AI Computing.
IEEE Pervasive Comput., 2024

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

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

Recurrent Early Exits for Federated Learning with Heterogeneous Clients.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Maestro: Uncovering Low-Rank Structures via Trainable Decomposition.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2022
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device.
ACM Trans. Embed. Comput. Syst., November, 2022

Federated Learning for Inference at Anytime and Anywhere.
CoRR, 2022

Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs.
CoRR, 2022

FedorAS: Federated Architecture Search under system heterogeneity.
CoRR, 2022

Adaptable mobile vision systems through multi-exit neural networks.
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.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation.
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.
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.
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.
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.
Proceedings of the IMC '21: ACM Internet Measurement Conference, 2021

2020
SPINN: synergistic progressive inference of neural networks over device and cloud.
Proceedings of the MobiCom '20: The 26th Annual International Conference on Mobile Computing and Networking, 2020

HAPI: Hardware-Aware Progressive Inference.
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.
CoRR, 2019

ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning.
Proceedings of the 20th Annual Conference of the International Speech Communication Association, 2019


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