default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDStefanos Laskaridis
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c12]Samuel Horváth, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang:
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. ICML 2024- [c11]Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas Donald Lane:
Recurrent Early Exits for Federated Learning with Heterogeneous Clients. ICML 2024 - [i18]Dimitris Spathis, Aaqib Saeed, Ali Etemad, Sana Tonekaboni, Stefanos Laskaridis, Shohreh Deldari, Chi Ian Tang, Patrick Schwab, Shyam Tailor:
A collection of the accepted papers for the Human-Centric Representation Learning workshop at AAAI 2024. CoRR abs/2403.10561 (2024) - [i17]Stefanos Laskaridis, Kleomenis Katevas, Lorenzo Minto, Hamed Haddadi:
MELTing point: Mobile Evaluation of Language Transformers. CoRR abs/2403.12844 (2024) - [i16]Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane:
Recurrent Early Exits for Federated Learning with Heterogeneous Clients. CoRR abs/2405.14791 (2024) - 2023
- [e1]Stefanos Laskaridis, Alexey Tumanov, Nathalie Baracaldo, Dimitrios Vytiniotis:
Proceedings of the 4th International Workshop on Distributed Machine Learning, DistributedML 2023, Paris, France, 8 December 2023. ACM 2023 [contents] - [i15]Samuel Horváth
, Stefanos Laskaridis, Shashank Rajput, Hongyi Wang:
Maestro: Uncovering Low-Rank Structures via Trainable Decomposition. CoRR abs/2308.14929 (2023) - 2022
- [j1]Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane:
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. ACM Trans. Embed. Comput. Syst. 21(6): 71:1-71:24 (2022) - [c10]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Multi-Exit Semantic Segmentation Networks. ECCV (21) 2022: 330-349 - [c9]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Adaptable mobile vision systems through multi-exit neural networks. MobiSys 2022: 575-576 - [i14]Lukasz Dudziak, Stefanos Laskaridis, Javier Fernández-Marqués:
FedorAS: Federated Architecture Search under system heterogeneity. CoRR abs/2206.11239 (2022) - [i13]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Fluid Batching: Exit-Aware Preemptive Serving of Early-Exit Neural Networks on Edge NPUs. CoRR abs/2209.13443 (2022) - [i12]Stefanos Laskaridis, Stylianos I. Venieris, Alexandros Kouris, Rui Li, Nicholas D. Lane:
The Future of Consumer Edge-AI Computing. CoRR abs/2210.10514 (2022) - [i11]Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales:
Federated Learning for Inference at Anytime and Anywhere. CoRR abs/2212.04084 (2022) - 2021
- [c8]Mário Almeida, Stefanos Laskaridis, Abhinav Mehrotra, Lukasz Dudziak, Ilias Leontiadis, Nicholas D. Lane:
Smart at what cost?: characterising mobile deep neural networks in the wild. Internet Measurement Conference 2021: 658-672 - [c7]Stefanos Laskaridis, Dimitris Spathis, Mário Almeida:
Federated mobile sensing for activity recognition. MobiCom 2021: 858-859 - [c6]Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane:
Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions. EMDL@MobiSys 2021: 1-6 - [c5]Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane:
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. NeurIPS 2021: 12876-12889 - [c4]Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane:
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. HotMobile 2021: 15-21 - [i10]Ilias Leontiadis, Stefanos Laskaridis, Stylianos I. Venieris, Nicholas D. Lane:
It's always personal: Using Early Exits for Efficient On-Device CNN Personalisation. CoRR abs/2102.01393 (2021) - [i9]Samuel Horváth, Stefanos Laskaridis, Mário Almeida, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane:
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout. CoRR abs/2102.13451 (2021) - [i8]Mário Almeida, Stefanos Laskaridis, Stylianos I. Venieris, Ilias Leontiadis, Nicholas D. Lane:
DynO: Dynamic Onloading of Deep Neural Networks from Cloud to Device. CoRR abs/2104.09949 (2021) - [i7]Alexandros Kouris, Stylianos I. Venieris, Stefanos Laskaridis, Nicholas D. Lane:
Multi-Exit Semantic Segmentation Networks. CoRR abs/2106.03527 (2021) - [i6]Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane:
Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions. CoRR abs/2106.05022 (2021) - [i5]Mário Almeida, Stefanos Laskaridis, Abhinav Mehrotra, Lukasz Dudziak, Ilias Leontiadis, Nicholas D. Lane:
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild. CoRR abs/2109.13963 (2021) - 2020
- [c3]Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane:
HAPI: Hardware-Aware Progressive Inference. ICCAD 2020: 91:1-91:9 - [c2]Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane:
SPINN: synergistic progressive inference of neural networks over device and cloud. MobiCom 2020: 37:1-37:15 - [i4]Stefanos Laskaridis, Stylianos I. Venieris, Hyeji Kim, Nicholas D. Lane:
HAPI: Hardware-Aware Progressive Inference. CoRR abs/2008.03997 (2020) - [i3]Stefanos Laskaridis, Stylianos I. Venieris, Mário Almeida, Ilias Leontiadis, Nicholas D. Lane:
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud. CoRR abs/2008.06402 (2020)
2010 – 2019
- 2019
- [c1]Lukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla, Stefanos Laskaridis, Nicholas D. Lane:
ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning. INTERSPEECH 2019: 2235-2239 - [i2]Mário Almeida, Stefanos Laskaridis, Ilias Leontiadis, Stylianos I. Venieris, Nicholas D. Lane:
EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices. CoRR abs/1905.07346 (2019) - [i1]Lukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla, Stefanos Laskaridis, Nicholas D. Lane:
ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning. CoRR abs/1907.03540 (2019)
Coauthor Index
aka: Nicholas Donald Lane
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-09-04 00:29 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
