Stefanos Laskaridis

38 papers A* 6A 4Misc 1Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	FlexRank: Nested Low-Rank Knowledge Decomposition for Adaptive Model Deployment. CoRR Riccardo Zaccone, Stefanos Laskaridis, Marco Ciccone, Samuel Horváth
2026	J	`jnl`	MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models. CoRR Nurbek Tastan, Stefanos Laskaridis, Karthik Nandakumar, Samuel Horvath
2025	J	`jnl`	LoFT: Low-Rank Adaptation That Behaves Like Full Fine-Tuning. CoRR Nurbek Tastan, Stefanos Laskaridis, Martin Takác, Karthik Nandakumar, Samuel Horváth
2025	J	`jnl`	NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation. CoRR Rob Romijnders, Stefanos Laskaridis, Ali Shahin Shamsabadi, Hamed Haddadi
2024	J	`jnl`	A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024. CoRR Dimitris Spathis, Aaqib Saeed, Ali Etemad, Sana Tonekaboni, Stefanos Laskaridis, Shohreh Deldari, Chi Ian Tang, Patrick Schwab, Shyam A. Tailor
2024	A*	`conf`	MELTing Point: Mobile Evaluation of Language Transformers. MobiCom Stefanos Laskaridis, Kleomenis Katevas, Lorenzo Minto, Hamed Haddadi
2024	J	`jnl`	MELTing point: Mobile Evaluation of Language Transformers. CoRR Stefanos Laskaridis, Kleomenis Katevas, Lorenzo Minto, Hamed Haddadi
2024	A*	`conf`	Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. ICML Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang
2024	A*	`conf`	Recurrent Early Exits for Federated Learning with Heterogeneous Clients. ICML Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas Donald Lane
2024	J	`jnl`	Recurrent Early Exits for Federated Learning with Heterogeneous Clients. CoRR Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2024	J	`jnl`	The Future of Consumer Edge-AI Computing. IEEE Pervasive Comput. Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane
2023	J	`jnl`	Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. CoRR Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang
2023	—	`ed.`	Proceedings of the 4th International Workshop on Distributed Machine Learning, DistributedML 2023, Paris, France, 8 December 2023 DistributedML@CoNEXT Stefanos Laskaridis, Alexey Tumanov, Nathalie Baracaldo, Dimitrios Vytiniotis
2022	A	`conf`	Adaptable mobile vision systems through multi-exit neural networks. MobiSys Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2022	J	`jnl`	DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. ACM Trans. Embed. Comput. Syst. Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane
2022	J	`jnl`	Federated Learning for Inference at Anytime and Anywhere. CoRR Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales
2022	J	`jnl`	FedorAS: Federated Architecture Search under system heterogeneity. CoRR Lukasz Dudziak, Stefanos Laskaridis, Javier Fernández-Marqués
2022	J	`jnl`	Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs. CoRR Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2022	—	`conf`	Multi-Exit Semantic Segmentation Networks. ECCV (21) Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2022	J	`jnl`	The Future of Consumer Edge-AI Computing. CoRR Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane
2021	—	`conf`	Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions. EMDL@MobiSys Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane
2021	J	`jnl`	Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions. CoRR Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane
2021	J	`jnl`	DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. CoRR Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane
2021	A*	`conf`	Federated mobile sensing for activity recognition. MobiCom Stefanos Laskaridis, Dimitris Spathis, Mário Almeida
2021	A*	`conf`	FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. NeurIPS Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane
2021	J	`jnl`	FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. CoRR Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane
2021	Misc	`conf`	It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. HotMobile Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane
2021	J	`jnl`	It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. CoRR Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane
2021	J	`jnl`	Multi-Exit Semantic Segmentation Networks. CoRR Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane
2021	J	`jnl`	Smart at what cost? Characterising Mobile Deep Neural Networks in the wild. CoRR Mário Almeida, Stefanos Laskaridis, Abhinav Mehrotra, Lukasz Dudziak, Ilias Leontiadis, Nicholas D. Lane
2021	A	`conf`	Smart at what cost?: characterising mobile deep neural networks in the wild. Internet Measurement Conference Mário Almeida, Stefanos Laskaridis, Abhinav Mehrotra, Lukasz Dudziak, Ilias Leontiadis, Nicholas D. Lane
2020	A	`conf`	HAPI: Hardware-Aware Progressive Inference. ICCAD Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane
2020	J	`jnl`	HAPI: Hardware-Aware Progressive Inference. CoRR Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane
2020	J	`jnl`	SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud. CoRR Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane
2020	A*	`conf`	SPINN: synergistic progressive inference of neural networks over device and cloud. MobiCom Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane
2019	J	`jnl`	EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices. CoRR Mário Almeida, Stefanos Laskaridis, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane
2019	A	`conf`	ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning. INTERSPEECH Lukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla, Stefanos Laskaridis, Nicholas D. Lane
2019	J	`jnl`	ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning. CoRR Lukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla, Stefanos Laskaridis, Nicholas D. Lane