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Mário Almeida
Mário Almeida
VP of Engineering, Rain.us
Verified email at rain.us - Homepage
Title
Cited by
Cited by
Year
SPINN: synergistic progressive inference of neural networks over device and cloud
S Laskaridis, SI Venieris, M Almeida, I Leontiadis, ND Lane
Proceedings of the 26th annual international conference on mobile computing …, 2020
682020
RILAnalyzer: a comprehensive 3G monitor on your phone
N Vallina-Rodriguez, A Auçinas, M Almeida, Y Grunenberger, ...
Proceedings of the 2013 conference on Internet measurement conference, 257-264, 2013
622013
Stweeler: A Framework for Twitter Bot Analysis
Z Gilani, M Almeida, R Farahbakhsh, L Wang, J Crowcroft
Proceedings of the 25th International Conference Companion on World Wide Web …, 2016
572016
EmBench: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices
M Almeida, S Laskaridis, I Leontiadis, SI Venieris, ND Lane
2019 3rd International Workshop on Embedded and Mobile Deep Learning (EMDL …, 2019
522019
A family of droids-Android malware detection via behavioral modeling: Static vs dynamic analysis
L Onwuzurike, M Almeida, E Mariconti, J Blackburn, G Stringhini, ...
2018 16th Annual Conference on Privacy, Security and Trust (PST), 1-10, 2018
46*2018
Dissecting DNS Stakeholders in Mobile Networks
M Almeida, A Finamore, D Perino, N Vallina-Rodriguez, M Varvello
Proceedings of the 13th International Conference on Emerging Networking …, 2017
362017
Fjord: Fair and accurate federated learning under heterogeneous targets with ordered dropout
S Horvath, S Laskaridis, M Almeida, I Leontiadis, S Venieris, N Lane
Advances in Neural Information Processing Systems 34, 12876-12889, 2021
332021
Chimp: Crowdsourcing Human Inputs for Mobile Phones
M Almeida, M Bilal, A Finamore, I Leontiadis, Y Grunenberger, M Varvello, ...
Proceedings of the 2018 World Wide Web Conference, 45-54, 2018
312018
An empirical study of android alarm usage for application scheduling
M Almeida, M Bilal, J Blackburn, K Papagiannaki
International Conference on Passive and Active Network Measurement, 373-384, 2016
92016
Smart at what cost? Characterising Mobile Deep Neural Networks in the wild
M Almeida, S Laskaridis, A Mehrotra, L Dudziak, I Leontiadis, ND Lane
Proceedings of the 21st ACM Internet Measurement Conference, 658-672, 2021
82021
Dyno: Dynamic onloading of deep neural networks from cloud to device
M Almeida, S Laskaridis, SI Venieris, I Leontiadis, ND Lane
ACM Transactions on Embedded Computing Systems (TECS), 2021
82021
C3po: Computation congestion control (proactive)
L Wang, M Almeida, J Blackburn, J Crowcroft
Proceedings of the 3rd ACM Conference on Information-Centric Networking, 231-236, 2016
62016
Method, system and apparatus for federated learning
S Laskaridis, S Horvath, M Almeida, I Leontiadis, SI Venieris
US Patent App. 17/586,178, 2022
2022
Method and system for neural network execution distribution
M Almeida, S Laskaridis, S Venieris, I Leontiadis
US Patent App. 17/420,259, 2022
2022
DistributedML 2021: Chairs' Welcome Message
S Laskaridis, M Almeida, J Crowcroft, C Zhang, O Simeone
DistributedML 2021-Proceedings of the 2nd ACM International Workshop on …, 2021
2021
Federated mobile sensing for activity recognition
S Laskaridis, D Spathis, M Almeida
Proceedings of the 27th Annual International Conference on Mobile Computing …, 2021
2021
Diffusing Your Mobile Apps: Extending In-Network Function Virtualization to Mobile Function Offloading
M Almeida, L Wang, J Blackburn, K Papagiannaki, J Crowcroft
arXiv preprint arXiv:1906.06240, 2019
2019
Elastic phone: towards detecting and mitigating computation and energy inefficiencies in mobile apps
M Almeida
Universitat Politècnica de Catalunya, 2018
2018
Journal: Proceedings of the 26th Annual International Conference on Mobile Computing and Networking, 2020
S Laskaridis, SI Venieris, M Almeida, I Leontiadis, ND Lane
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Articles 1–19